Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce gree...Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce greenhouse gases and support ecological balance.In this study,geographic information system(GIS)predictive analysis was employed to explore geothermal prospects,promoting environmental sustainability by reducing the dependence on fossil energy resources.Spatial and statistical analysis including the attribute correlation analysis was used to evaluate the relationship between exploration data and geothermal energy resources represented by hot springs.The weighted sum model was then used to develop geothermal predictive maps while the accuracy of prediction was determined using the receiver operating characteristic/area under curve(ROC/AUC)analysis.Based on the attribute correlation analysis,exploration data relating to geological structures,host rock(Asu River Group)and sedimentary contacts were the most critical parameters for mapping geothermal resources.These parameters were characterized by a statistical association of 0.52,0.48,and 0.46 with the known geothermal occurrences.Spatial data integration reveals the central part of the study location as the most prospective zone for geothermal occurrences.This zone occupies 14.76%of the study location.Accuracy assessment using the ROC/AUC analysis suggests an efficiency of 81.5%for the weight sum model.GIS-based multi-criteria analysis improves the identification and evaluation of geothermal resources,leading to better decision-making.展开更多
Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy ...Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy logic,and multi-criteria decision-making(MCDM)in transportation research.A comprehensive literature search was conducted in the Scopus database,utilizing carefully selected AI,fuzzy,and MCDM keywords.Studies were rigorously screened according to explicit inclusion and exclusion criteria,resulting in 73 eligible publications spanning 2006-2025.The review protocol included transparent data extraction on methodological approaches,application domains,and geographic distribution.Key findings highlight the prevalence of hybrid fuzzyAHPand TOPSIS methods,the widespread integration of machine learning for prediction and optimization,and a predominant focus on logistics and infrastructure planning within the transportation sector.Geographic analysis underscores a marked concentration of research activity in Asia,while other regions remain underrepresented,signaling the need for broader international collaboration.The review also addresses persistent challenges such asmethodological complexity,data limitations,and model interpretability.Future research directions are proposed,including the integration of reinforcement learning,real-time analytics,and big data-driven adaptive solutions.This study offers a comprehensive synthesis and critical perspective,serving as a valuable reference for researchers,practitioners,and policymakers seeking to enhance the efficiency,resilience,and sustainability of transportation systems through intelligent decision-making frameworks.展开更多
Objective To evaluate the clinical value of siltuximab in the treatment of Castleman disease based on multicriteria decision analysis(MCDA)and evidence and value:Impact on decision making(EVIDEM)framework.Methods The ...Objective To evaluate the clinical value of siltuximab in the treatment of Castleman disease based on multicriteria decision analysis(MCDA)and evidence and value:Impact on decision making(EVIDEM)framework.Methods The evidence matrix for quantitative analysis of MCDA was extracted through literature research,and the weight of each evaluation index was calculated by the maximum differentiation measure in conjoint analysis.Besides,the clinical value of siltuximab in the treatment of Castleman disease was analyzed quantitatively and qualitatively based on the results of expert questionnaire surveys.Results and Conclusion The clinical value score of siltuximab was 0.491,and the weight ratio of“therapeutic benefit”(15.39%),“drug effectiveness”(14.46%)and“drug safety”(11.43%)were the three largest.Among the indexes of“drug effectiveness”“drug safety”“patient reported outcome”“therapeutic benefit”and“non-medical cost”,siltuximab for Castleman disease was considered to be a more valuable treatment option than other first-line therapies.By qualitative analysis,57%experts believed that siltuximab was a better treatment option.The indexes that contribute the most to the overall clinical value of siltuximab are“therapeutic benefit”“drug effectiveness”and“quality of evidence”,while the indexes that have a negative impact on the clinical value of siltuximab is“drug treatment cost”.展开更多
Floods are one of the most frequent natural hazards worldwide.Accurate flood risk mapping is critical for eff ective flood management in flood-prone areas.In this study,we employed the multi-criteria decision analysis...Floods are one of the most frequent natural hazards worldwide.Accurate flood risk mapping is critical for eff ective flood management in flood-prone areas.In this study,we employed the multi-criteria decision analysis(MCDA)method to develop a flood risk map that combines flood susceptibility and vulnerability factors.Three machine learning models—random forest(RF),XGBoost,and LightGBM—were selected as the basic classifiers for creating flood susceptibility maps.Historical flood data and 13 flood-influencing factors were extracted for machine learning training.Model performance was assessed using precision,recall,accuracy,F1-score,and AUC through 5-fold cross-validation.All three models performed well,but RF slightly outperformed the other two according to the evaluation results.We used the analytic hierarchy process(AHP)method to combine the flood susceptibility map generated by the RF model with flood vulnerability indicators to produce a flood risk map.Our findings demonstrate that integrating advanced machine learning techniques with MCDA method off ers an eff ective approach for flood risk assessment,providing a robust foundation for decision making in flood risk management.展开更多
Judicious selection of landfill allocation is crucial since inappropriate dumping of wastes can negatively impact human health and degrade the ecosystem.Therefore,this survey presents an integration multi-criteria dec...Judicious selection of landfill allocation is crucial since inappropriate dumping of wastes can negatively impact human health and degrade the ecosystem.Therefore,this survey presents an integration multi-criteria decision approach with the geographic information system for re-evaluating the pending hazardous landfill in Jradou,Tunisia,considering the conflict with neighboring inhabitants.The study involved twelve constraints and eight factors relevant to environmental and socio-economic challenges based on international works,guidelines of the country’s legislation,and an assessment questionnaire on the landfill suitability map.The Analytic Hierarchy Process(AHP)apportioned weights to criteria,and a Weighted Linear Combination(WLC)approach generated landfill suitability maps(LSM).Afterward,the produced LSM revealed that 2%(8.46km²)of the land was classified as very high,followed by 48%(203.04km²)as high,25%(105.75km²)as moderate,10%(42.3km²)as low,and the remaining 15%(63.45km²)as very low suitable.Furthermore,the operating hazardous waste landfill of Jradou falls within unsuitable areas,inflicting severe harm on the neighboring.The pending hazardous landfill of Jradou should be closed,and a new site must be identified.Conversely,the highly suitable classes are further identified in(1)the Eastern part of the study area,near Ouled ben Amara,and(2)the Northern part of Zaghouan,at 2 km north of Smenja,for potential future hazardous waste landfills.Consequently,governments and relevant stakeholders should investigate these zones to locate new landfills.展开更多
A semantics-based model is proposed to enable weakened hedges, such as ＂more or less＂ and ＂roughly＂ in the context of linguistic multi-criteria decision making. First, the resemblance relations are defined based o...A semantics-based model is proposed to enable weakened hedges, such as ＂more or less＂ and ＂roughly＂ in the context of linguistic multi-criteria decision making. First, the resemblance relations are defined based on the semantics of terms on the domain. Then, the hedges can be represented after the upper and loose upper approximations of a linguistic term are derived. Accordingly, some compact formulae can be derived for the semantics of linguistic expressions with hedges. Parameters in these formulae are objectively determined according to the semantics of original terms. The proposed model presents a more natural way to express the decision information under uncertainties and its semantics is clear. The proposed model is clarified by solving the problem of evaluation and selection of sustainable innovative energy technologies. Computational results demonstrate that the model can deal with various uncertainties of the problem. Finally, the model is compared with existing techniques and extended to the case when the semantics of terms are represented by trapezoidal fuzzy numbers.展开更多
This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the lim...This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.展开更多
Intuitionistic trapezoidal fuzzy numbers and their operational laws are defined. Based on these operational laws, some aggregation operators, including intuitionistic trapezoidal fuzzy weighted arithmetic averaging op...Intuitionistic trapezoidal fuzzy numbers and their operational laws are defined. Based on these operational laws, some aggregation operators, including intuitionistic trapezoidal fuzzy weighted arithmetic averaging operator and weighted geometric averaging operator are proposed. Expected values, score function, and accuracy function of intuitionitsic trapezoidal fuzzy numbers are defined. Based on these, a kind of intuitionistic trapezoidal fuzzy multi-criteria decision making method is proposed. By using these aggregation operators, criteria values are aggregated and integrated intuitionistic trapezoidal fuzzy numbers of alternatives are attained. By comparing score function and accuracy function values of integrated fuzzy numbers, a ranking of the whole alternative set can be attained. An example is given to show the feasibility and availability of the method.展开更多
Urban construction land suitability evaluation （UCLSE） is a complex system engineering and the basis for rational use of the limited urban land resources in China. It has an important practical value on urban constr...Urban construction land suitability evaluation （UCLSE） is a complex system engineering and the basis for rational use of the limited urban land resources in China. It has an important practical value on urban construction land use planning and management from the angle of methodology. As a widely used technique, traditional multi-criteria evaluation based on GIS （MCE-GIS）, is not suitable for UCLSE. This study develops an improved MCE-GIS method which could be more suitable for UCLSE based on urban complex ecological system theory and the summary of the shortcomings of traditional MCE-GIS. The improvements include three aspects： a composite evaluation index system rather than natural indexes alone, an index weight calculated by using fuzzy Analytic Hierarchy Process （AHP） method rather than the common AHP method, and the integrated overlay rule, which includes selecting the minimum value, weighted linear combination （WLC） and simple summation. The main advantage of this improved technique is that it can make UCLSE more comprehensive, more operational and more reasonable. It can provide a scientific basis for decision making in the planning and management of urban construction land use. The improved MCE-GIS system has been adopted in the New Hefei City, Anhui Province, China. Based on the results of UCLSE in New Hefei, three functional areas including construction-appropriate areas, construction-restricted areas and construction-forbidden areas could be worked out, in which 36.90% of the total study area could be developed as urban construction land and the remaining 63.10% should be protected as reserves land or as ecological land. Furthermore, the results can orovide scientific decision suooort for spatial planning and eco-environment nrotection in New Hefei.展开更多
Proper solid waste disposal is an important socioeconomic concern for all developing countries.Municipalities have their own policies,individual approaches and methods to manage the solid wastes.They consider wastelan...Proper solid waste disposal is an important socioeconomic concern for all developing countries.Municipalities have their own policies,individual approaches and methods to manage the solid wastes.They consider wastelands outside the urban area as the best suitable for the solid waste disposal.Such improper site selection will create morphological changes that lead to environmental hazards in the urban and its surrounding areas.In this research,the site selection for urban solid waste disposal in the Coimbatore district used geographical information system(GIS)and multi-criteria decision analysis(MCDA).Thematic layers of lineament density,landuse/landcover,population density,groundwater depth,drainage density,slope,soil texture,geology and geomorphology were considered as primary criteria and weights for criteria,and sub-criteria were assigned by MCDA analysis.The resultant weight score was validated by consistency ratio so that the efficiency of the selected criteria was justified.The overlay analysis in GIS environment provides 17 potential zones in Coimbatore district,among which,four suitable sites were screened and refined with the help of field investigation and visual interpretation of satellite image.The result of landfill suitability map shows the effectiveness of the proposed method.展开更多
It is not uncommon in multiple criteria decision-making that the numerical values of alternatives of some criteria are subject to imprecision, uncertainty and indetermination and the information on weights of criteria...It is not uncommon in multiple criteria decision-making that the numerical values of alternatives of some criteria are subject to imprecision, uncertainty and indetermination and the information on weights of criteria is incomplete certain. A new multiple criteria decision- making method with incomplete certain information based on ternary AHP is proposed. This improves on Takeda＇s method. In this method, the ternary comparison matrix of the alternatives under each pseudo-criteria is constructed, the eigenvector associated with the maximum eigenvalue of the ternary comparison matrix is attained as to normalize priority vector of the alternatives, then the order of alternatives is obtained by solving two kinds of linear programming problems. Finally, an example is given to show the feasibility and effectiveness of the method.展开更多
We study a multi-criteria fuzzy decision-making method based on weighted triangular intuitionistic fuzzy number correlation coefficients. Under the scenario that criteria weights for alternatives are completely unknow...We study a multi-criteria fuzzy decision-making method based on weighted triangular intuitionistic fuzzy number correlation coefficients. Under the scenario that criteria weights for alternatives are completely unknown, triangular intuitionistic fuzzy method can not only supplement the insufficiency of the method based on the distance but also endow more information to the estimation and reduce the loss of evaluation information.Among the triangular numbers, two boundary numbers are the maximum and minimum values of the interval respectively, and the medium number is the most possible value under subjective estimation. Using this method,we propose a new way to obtain the criteria weights with more information quantity. By ranking the relative closeness of the weighted correlation coefficients between each alternative, and the critical and ideal alternatives,we show the method to figure out the most suitable alternative based on the expected criteria. An illustrative example is also taken into account to prove the effectiveness of the model.展开更多
Improper land use results in land degradation as well as decline in agricultural productivity.To obtain optimum benefit from the land,proper utilization of its resources is necessary.Land suitability analysis is the e...Improper land use results in land degradation as well as decline in agricultural productivity.To obtain optimum benefit from the land,proper utilization of its resources is necessary.Land suitability analysis is the evaluation and grouping of specific areas of land in terms of their suitability for a defined use,which is a precondition for sustainable land use planning.This study investigated the applicability of Geographical Information System(GIS)techniques in combination with multi-criteria land evaluation for analysing land suitability.The study used the weighted overlay technique for multi-criteria evaluation with GIS for the assessment of suitability of wheat cultivation in Beko watershed(Purulia,India).The watershed area is moderately suitable for wheat crop production,with constraints like imperfect drainage and poor soil depth.展开更多
A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the ...A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.展开更多
For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference informa...For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.展开更多
The VIKOR method is a multi-criteria decision making aid, which employs linear normalization to offer compromise solu- tions and has been successfully applied to various group decision making problems. However, the co...The VIKOR method is a multi-criteria decision making aid, which employs linear normalization to offer compromise solu- tions and has been successfully applied to various group decision making problems. However, the conventional VIKOR techniques used to integrate group judgments and the information loss arising from defuzzification are problematic and distort final outcomes. An improved integration method, which is optimization-based, is proposed. And it can handle fuzzy criteria values and weights. The precondition for accurately defuzzifying triangular fuzzy num- bers is identified. Several effective defuzzification procedures are proposed to improve the extant VIKOR, and a comprehensive evaluation framework is offered to aid multi-criteria group decision making. Finally, a numerical example is provided to illustrate the practicability of the proposed method.展开更多
The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evident...The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.展开更多
Molecular microbiological methods, such as competetive PCR, real-time PCR, denaturing gradient gel electrophoresis (DGGE) and large-scale parallel-pyrosequencing, require the extraction of sufficient quantity of high ...Molecular microbiological methods, such as competetive PCR, real-time PCR, denaturing gradient gel electrophoresis (DGGE) and large-scale parallel-pyrosequencing, require the extraction of sufficient quantity of high quality DNA from microbiologically and chemically complex matrices. Due to difficulties in the field to standardize/select the optimum DNA preservation-extraction methods in view of laboratories differences, this article attempts to present a straight-forward mathematical framework for comparing some of the most commonly used methods. To this end, as a case study, the problem of selecting an optimum sample preservation-DNA extraction strategy for obtaining total bacterial DNA from swine feces was considered. Two sample preservation methods (liquid nitrogen and RNAlater?) and seven extraction techniques were paired and compared under six quantitative DNA analysis criteria: yield of extraction, purity of extracted DNA (A260/280 and A 260/230 ratios), duration of extraction, degradation degree of DNA, and cost. From a practical point of view, it is unlikely that a single sample preservation-DNA extraction strategy can be optimum for all selected criteria. Hence, a systematic multi-criteria decision-making (MCDM) approach was used to compare the methods. As a result, the ZR Fecal DNA MiniPrepTM DNA extraction kit for samples preserved either with liquid nitrogen or RNAlater? were identified as potential optimum solutions for obtaining total bacterial DNA from swine feces. Considering the need for practicality for in situ applications, we would recommend liquid nitrogen as sample preservation method, along with the ZR Fecal DNA MiniPrepTM kit. Total bacterial DNA obtained by this strategy can be suitable for downstream PCR-based DNA analyses of swine feces.展开更多
Natural resources management is indispensable in ensuring environmental sustainability and reducing the risk associated with climate change and increasing demand for ecological goods and services. Natural resources pl...Natural resources management is indispensable in ensuring environmental sustainability and reducing the risk associated with climate change and increasing demand for ecological goods and services. Natural resources planners need to have at their disposal tools that can objectively help in prioritizing land use allocation. Traditional application of land use change model based on economic model, trend analysis, and or scenario analysis present some challenges of data availability and reliability necessary for implementation of the models. However, with the advent of information technology, GIS and remote sensing, biophysical data known for having influence on land use allocation can easily be accessed. The current study explores the application of GIS-Multi-criteria analysis in modeling future land use scenarios for resources planning and management using easy to construct biophysical parameters known for influencing future land use allocation. The decision problems in this study are to find the best spatial allocation of land to future agriculture and forest development, which are considered to present critical land use change in the study area. The afforestation scenarios are meant to offset the pressure on the native forest resources due to the increased demand for fuel and timber and also to contribute to the environmental protection and the agricultural land use scenarios are meant to increase productivity and ensure environmental protection. The land use scenarios did not consider “when” in the future the land use pattern may develop. The analyses of scenarios indicate that afforestation extent in the basin can be increased from 4.6% to 42.9% of the total basin area. However, the afforestation extent of 42.9% may be considered unrealistic, since in practice, it may not be possible to realize up to 42.9% afforestation, nevertheless, the spatial pattern of the afforestation may provide crucial insight into spatial afforestation policies and it future consequences. The agricultural land use can increase from 6.2% to 53.7% of the basin area. The agricultural land use expansion can be realised since the expansion of farm land is primarily the main option to achieve food production increase in the near future. The findings indicate potential use of the methodology in land use planning.展开更多
The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to st...The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.展开更多
文摘Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce greenhouse gases and support ecological balance.In this study,geographic information system(GIS)predictive analysis was employed to explore geothermal prospects,promoting environmental sustainability by reducing the dependence on fossil energy resources.Spatial and statistical analysis including the attribute correlation analysis was used to evaluate the relationship between exploration data and geothermal energy resources represented by hot springs.The weighted sum model was then used to develop geothermal predictive maps while the accuracy of prediction was determined using the receiver operating characteristic/area under curve(ROC/AUC)analysis.Based on the attribute correlation analysis,exploration data relating to geological structures,host rock(Asu River Group)and sedimentary contacts were the most critical parameters for mapping geothermal resources.These parameters were characterized by a statistical association of 0.52,0.48,and 0.46 with the known geothermal occurrences.Spatial data integration reveals the central part of the study location as the most prospective zone for geothermal occurrences.This zone occupies 14.76%of the study location.Accuracy assessment using the ROC/AUC analysis suggests an efficiency of 81.5%for the weight sum model.GIS-based multi-criteria analysis improves the identification and evaluation of geothermal resources,leading to better decision-making.
文摘Transportation systems are rapidly transforming in response to urbanization,sustainability challenges,and advances in digital technologies.This review synthesizes the intersection of artificial intelligence(AI),fuzzy logic,and multi-criteria decision-making(MCDM)in transportation research.A comprehensive literature search was conducted in the Scopus database,utilizing carefully selected AI,fuzzy,and MCDM keywords.Studies were rigorously screened according to explicit inclusion and exclusion criteria,resulting in 73 eligible publications spanning 2006-2025.The review protocol included transparent data extraction on methodological approaches,application domains,and geographic distribution.Key findings highlight the prevalence of hybrid fuzzyAHPand TOPSIS methods,the widespread integration of machine learning for prediction and optimization,and a predominant focus on logistics and infrastructure planning within the transportation sector.Geographic analysis underscores a marked concentration of research activity in Asia,while other regions remain underrepresented,signaling the need for broader international collaboration.The review also addresses persistent challenges such asmethodological complexity,data limitations,and model interpretability.Future research directions are proposed,including the integration of reinforcement learning,real-time analytics,and big data-driven adaptive solutions.This study offers a comprehensive synthesis and critical perspective,serving as a valuable reference for researchers,practitioners,and policymakers seeking to enhance the efficiency,resilience,and sustainability of transportation systems through intelligent decision-making frameworks.
文摘Objective To evaluate the clinical value of siltuximab in the treatment of Castleman disease based on multicriteria decision analysis(MCDA)and evidence and value:Impact on decision making(EVIDEM)framework.Methods The evidence matrix for quantitative analysis of MCDA was extracted through literature research,and the weight of each evaluation index was calculated by the maximum differentiation measure in conjoint analysis.Besides,the clinical value of siltuximab in the treatment of Castleman disease was analyzed quantitatively and qualitatively based on the results of expert questionnaire surveys.Results and Conclusion The clinical value score of siltuximab was 0.491,and the weight ratio of“therapeutic benefit”(15.39%),“drug effectiveness”(14.46%)and“drug safety”(11.43%)were the three largest.Among the indexes of“drug effectiveness”“drug safety”“patient reported outcome”“therapeutic benefit”and“non-medical cost”,siltuximab for Castleman disease was considered to be a more valuable treatment option than other first-line therapies.By qualitative analysis,57%experts believed that siltuximab was a better treatment option.The indexes that contribute the most to the overall clinical value of siltuximab are“therapeutic benefit”“drug effectiveness”and“quality of evidence”,while the indexes that have a negative impact on the clinical value of siltuximab is“drug treatment cost”.
基金funded by the National Key Research and Development Project(Grant No.2021YFB3901203)the Research grant from the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant No.2023-JBKY-58)。
文摘Floods are one of the most frequent natural hazards worldwide.Accurate flood risk mapping is critical for eff ective flood management in flood-prone areas.In this study,we employed the multi-criteria decision analysis(MCDA)method to develop a flood risk map that combines flood susceptibility and vulnerability factors.Three machine learning models—random forest(RF),XGBoost,and LightGBM—were selected as the basic classifiers for creating flood susceptibility maps.Historical flood data and 13 flood-influencing factors were extracted for machine learning training.Model performance was assessed using precision,recall,accuracy,F1-score,and AUC through 5-fold cross-validation.All three models performed well,but RF slightly outperformed the other two according to the evaluation results.We used the analytic hierarchy process(AHP)method to combine the flood susceptibility map generated by the RF model with flood vulnerability indicators to produce a flood risk map.Our findings demonstrate that integrating advanced machine learning techniques with MCDA method off ers an eff ective approach for flood risk assessment,providing a robust foundation for decision making in flood risk management.
基金This research was supported by Researchers Supporting Project number(RSP2025R425),King Saud University,Riyadh,Saudi Arabia.
文摘Judicious selection of landfill allocation is crucial since inappropriate dumping of wastes can negatively impact human health and degrade the ecosystem.Therefore,this survey presents an integration multi-criteria decision approach with the geographic information system for re-evaluating the pending hazardous landfill in Jradou,Tunisia,considering the conflict with neighboring inhabitants.The study involved twelve constraints and eight factors relevant to environmental and socio-economic challenges based on international works,guidelines of the country’s legislation,and an assessment questionnaire on the landfill suitability map.The Analytic Hierarchy Process(AHP)apportioned weights to criteria,and a Weighted Linear Combination(WLC)approach generated landfill suitability maps(LSM).Afterward,the produced LSM revealed that 2%(8.46km²)of the land was classified as very high,followed by 48%(203.04km²)as high,25%(105.75km²)as moderate,10%(42.3km²)as low,and the remaining 15%(63.45km²)as very low suitable.Furthermore,the operating hazardous waste landfill of Jradou falls within unsuitable areas,inflicting severe harm on the neighboring.The pending hazardous landfill of Jradou should be closed,and a new site must be identified.Conversely,the highly suitable classes are further identified in(1)the Eastern part of the study area,near Ouled ben Amara,and(2)the Northern part of Zaghouan,at 2 km north of Smenja,for potential future hazardous waste landfills.Consequently,governments and relevant stakeholders should investigate these zones to locate new landfills.
基金The National Natural Science Foundation of China(No.61273209)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1528)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX15-0191)
文摘A semantics-based model is proposed to enable weakened hedges, such as ＂more or less＂ and ＂roughly＂ in the context of linguistic multi-criteria decision making. First, the resemblance relations are defined based on the semantics of terms on the domain. Then, the hedges can be represented after the upper and loose upper approximations of a linguistic term are derived. Accordingly, some compact formulae can be derived for the semantics of linguistic expressions with hedges. Parameters in these formulae are objectively determined according to the semantics of original terms. The proposed model presents a more natural way to express the decision information under uncertainties and its semantics is clear. The proposed model is clarified by solving the problem of evaluation and selection of sustainable innovative energy technologies. Computational results demonstrate that the model can deal with various uncertainties of the problem. Finally, the model is compared with existing techniques and extended to the case when the semantics of terms are represented by trapezoidal fuzzy numbers.
文摘This paper proposes a multi-criteria decision-making (MCGDM) method based on the improved single-valued neutrosophic Hamacher weighted averaging (ISNHWA) operator and grey relational analysis (GRA) to overcome the limitations of present methods based on aggregation operators. First, the limitations of several existing single-valued neutrosophic weighted averaging aggregation operators (i.e. , the single-valued neutrosophic weighted averaging, single-valued neutrosophic weighted algebraic averaging, single-valued neutrosophic weighted Einstein averaging, single-valued neutrosophic Frank weighted averaging, and single-valued neutrosophic Hamacher weighted averaging operators), which can produce some indeterminate terms in the aggregation process, are discussed. Second, an ISNHWA operator was developed to overcome the limitations of existing operators. Third, the properties of the proposed operator, including idempotency, boundedness, monotonicity, and commutativity, were analyzed. Application examples confirmed that the ISNHWA operator and the proposed MCGDM method are rational and effective. The proposed improved ISNHWA operator and MCGDM method can overcome the indeterminate results in some special cases in existing single-valued neutrosophic weighted averaging aggregation operators and MCGDM methods.
基金supported by the National Natural Science Foundation of China (70771115).
文摘Intuitionistic trapezoidal fuzzy numbers and their operational laws are defined. Based on these operational laws, some aggregation operators, including intuitionistic trapezoidal fuzzy weighted arithmetic averaging operator and weighted geometric averaging operator are proposed. Expected values, score function, and accuracy function of intuitionitsic trapezoidal fuzzy numbers are defined. Based on these, a kind of intuitionistic trapezoidal fuzzy multi-criteria decision making method is proposed. By using these aggregation operators, criteria values are aggregated and integrated intuitionistic trapezoidal fuzzy numbers of alternatives are attained. By comparing score function and accuracy function values of integrated fuzzy numbers, a ranking of the whole alternative set can be attained. An example is given to show the feasibility and availability of the method.
基金Under the auspices of National Natural Science Foundation of China(No.41201168)Fundamental Research Funds for the Central Universities(No.2013HGXJ0207)
文摘Urban construction land suitability evaluation （UCLSE） is a complex system engineering and the basis for rational use of the limited urban land resources in China. It has an important practical value on urban construction land use planning and management from the angle of methodology. As a widely used technique, traditional multi-criteria evaluation based on GIS （MCE-GIS）, is not suitable for UCLSE. This study develops an improved MCE-GIS method which could be more suitable for UCLSE based on urban complex ecological system theory and the summary of the shortcomings of traditional MCE-GIS. The improvements include three aspects： a composite evaluation index system rather than natural indexes alone, an index weight calculated by using fuzzy Analytic Hierarchy Process （AHP） method rather than the common AHP method, and the integrated overlay rule, which includes selecting the minimum value, weighted linear combination （WLC） and simple summation. The main advantage of this improved technique is that it can make UCLSE more comprehensive, more operational and more reasonable. It can provide a scientific basis for decision making in the planning and management of urban construction land use. The improved MCE-GIS system has been adopted in the New Hefei City, Anhui Province, China. Based on the results of UCLSE in New Hefei, three functional areas including construction-appropriate areas, construction-restricted areas and construction-forbidden areas could be worked out, in which 36.90% of the total study area could be developed as urban construction land and the remaining 63.10% should be protected as reserves land or as ecological land. Furthermore, the results can orovide scientific decision suooort for spatial planning and eco-environment nrotection in New Hefei.
文摘Proper solid waste disposal is an important socioeconomic concern for all developing countries.Municipalities have their own policies,individual approaches and methods to manage the solid wastes.They consider wastelands outside the urban area as the best suitable for the solid waste disposal.Such improper site selection will create morphological changes that lead to environmental hazards in the urban and its surrounding areas.In this research,the site selection for urban solid waste disposal in the Coimbatore district used geographical information system(GIS)and multi-criteria decision analysis(MCDA).Thematic layers of lineament density,landuse/landcover,population density,groundwater depth,drainage density,slope,soil texture,geology and geomorphology were considered as primary criteria and weights for criteria,and sub-criteria were assigned by MCDA analysis.The resultant weight score was validated by consistency ratio so that the efficiency of the selected criteria was justified.The overlay analysis in GIS environment provides 17 potential zones in Coimbatore district,among which,four suitable sites were screened and refined with the help of field investigation and visual interpretation of satellite image.The result of landfill suitability map shows the effectiveness of the proposed method.
文摘It is not uncommon in multiple criteria decision-making that the numerical values of alternatives of some criteria are subject to imprecision, uncertainty and indetermination and the information on weights of criteria is incomplete certain. A new multiple criteria decision- making method with incomplete certain information based on ternary AHP is proposed. This improves on Takeda＇s method. In this method, the ternary comparison matrix of the alternatives under each pseudo-criteria is constructed, the eigenvector associated with the maximum eigenvalue of the ternary comparison matrix is attained as to normalize priority vector of the alternatives, then the order of alternatives is obtained by solving two kinds of linear programming problems. Finally, an example is given to show the feasibility and effectiveness of the method.
基金the National Natural Science Foundation of China(Nos.71671016,71231001 and 71832001)the Fundamental Research Funds for the Central Universities of China(No.FRF-BR-15-001B)
文摘We study a multi-criteria fuzzy decision-making method based on weighted triangular intuitionistic fuzzy number correlation coefficients. Under the scenario that criteria weights for alternatives are completely unknown, triangular intuitionistic fuzzy method can not only supplement the insufficiency of the method based on the distance but also endow more information to the estimation and reduce the loss of evaluation information.Among the triangular numbers, two boundary numbers are the maximum and minimum values of the interval respectively, and the medium number is the most possible value under subjective estimation. Using this method,we propose a new way to obtain the criteria weights with more information quantity. By ranking the relative closeness of the weighted correlation coefficients between each alternative, and the critical and ideal alternatives,we show the method to figure out the most suitable alternative based on the expected criteria. An illustrative example is also taken into account to prove the effectiveness of the model.
文摘Improper land use results in land degradation as well as decline in agricultural productivity.To obtain optimum benefit from the land,proper utilization of its resources is necessary.Land suitability analysis is the evaluation and grouping of specific areas of land in terms of their suitability for a defined use,which is a precondition for sustainable land use planning.This study investigated the applicability of Geographical Information System(GIS)techniques in combination with multi-criteria land evaluation for analysing land suitability.The study used the weighted overlay technique for multi-criteria evaluation with GIS for the assessment of suitability of wheat cultivation in Beko watershed(Purulia,India).The watershed area is moderately suitable for wheat crop production,with constraints like imperfect drainage and poor soil depth.
基金supported by the National Natural Science Foundation of China (60904059 60975049)+1 种基金the Philosophy and Social Science Foundation of Hunan Province (2010YBA104)the National High Technology Research and Development Program of China (863 Program)(2009AA04Z107)
文摘A method of minimizing rankings inconsistency is proposed for a decision-making problem with rankings of alternatives given by multiple decision makers according to multiple criteria. For each criteria, at first, the total inconsistency between the rankings of all alternatives for the group and the ones for every decision maker is defined after the decision maker weights in respect to the criteria are considered. Similarly, the total inconsistency between their final rankings for the group and the ones under every criteria is determined after the criteria weights are taken into account. Then two nonlinear integer programming models minimizing respectively the two total inconsistencies above are developed and then transformed to two dynamic programming models to obtain separately the rankings of all alternatives for the group with respect to each criteria and their final rankings. A supplier selection case illustrated the proposed method, and some discussions on the results verified its effectiveness. This work develops a new measurement of ordinal preferences’ inconsistency in multi-criteria group decision-making （MCGDM） and extends the cook-seiford social selection function to MCGDM considering weights of criteria and decision makers and can obtain unique ranking result.
基金the Key Project of National Natural Science Foundation of China (70631004)the National Natural Science Foundation of China (70771115)
文摘For group decision-making problems with linguistic assessment information, a new method based on two-tuple and WC-OWA operator is proposed, in which the criteria＇s weights and the decision-makers＇ preference information might take the form of linguistic grade, or might be between two continuous linguistic grades, or might be linguistic interval, or might be default. In this method, all linguistic values are transformed into two-tuple, and an aggregative decision-making matrix is obtained by using interval operation. The group aggregative values of each criterion on alternatives are computed by using a WC-OWA operator, the aggregative values on alternatives are worked out, and transformed into two-tuple. And the rank of the alternatives is obtained by using the order property of two-tuple. An example shows the feasibility and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(71271116)
文摘The VIKOR method is a multi-criteria decision making aid, which employs linear normalization to offer compromise solu- tions and has been successfully applied to various group decision making problems. However, the conventional VIKOR techniques used to integrate group judgments and the information loss arising from defuzzification are problematic and distort final outcomes. An improved integration method, which is optimization-based, is proposed. And it can handle fuzzy criteria values and weights. The precondition for accurately defuzzifying triangular fuzzy num- bers is identified. Several effective defuzzification procedures are proposed to improve the extant VIKOR, and a comprehensive evaluation framework is offered to aid multi-criteria group decision making. Finally, a numerical example is provided to illustrate the practicability of the proposed method.
基金supported by the National Natural Science Foundation of China(7077111570921001)and Key Project of National Natural Science Foundation of China(70631004)
文摘The weights of criteria are incompletely known and the criteria values are incomplete and uncertain or even default in some fuzzy multi-criteria decision-making problems.For those problems,an approach based on evidential reasoning is proposed,in which the criteria values are integrated on the basis of analytical algorithm of evidential reasoning,and then nonlinear programming models of each alternative are developed with the incomplete information on weights.The genetic algorithm is employed to solve the models,producing the weights and the utility interval of each alternative,and the ranking of the whole set of alternatives can be attained.Finally,an example shows the effectiveness of the method.
文摘Molecular microbiological methods, such as competetive PCR, real-time PCR, denaturing gradient gel electrophoresis (DGGE) and large-scale parallel-pyrosequencing, require the extraction of sufficient quantity of high quality DNA from microbiologically and chemically complex matrices. Due to difficulties in the field to standardize/select the optimum DNA preservation-extraction methods in view of laboratories differences, this article attempts to present a straight-forward mathematical framework for comparing some of the most commonly used methods. To this end, as a case study, the problem of selecting an optimum sample preservation-DNA extraction strategy for obtaining total bacterial DNA from swine feces was considered. Two sample preservation methods (liquid nitrogen and RNAlater?) and seven extraction techniques were paired and compared under six quantitative DNA analysis criteria: yield of extraction, purity of extracted DNA (A260/280 and A 260/230 ratios), duration of extraction, degradation degree of DNA, and cost. From a practical point of view, it is unlikely that a single sample preservation-DNA extraction strategy can be optimum for all selected criteria. Hence, a systematic multi-criteria decision-making (MCDM) approach was used to compare the methods. As a result, the ZR Fecal DNA MiniPrepTM DNA extraction kit for samples preserved either with liquid nitrogen or RNAlater? were identified as potential optimum solutions for obtaining total bacterial DNA from swine feces. Considering the need for practicality for in situ applications, we would recommend liquid nitrogen as sample preservation method, along with the ZR Fecal DNA MiniPrepTM kit. Total bacterial DNA obtained by this strategy can be suitable for downstream PCR-based DNA analyses of swine feces.
文摘Natural resources management is indispensable in ensuring environmental sustainability and reducing the risk associated with climate change and increasing demand for ecological goods and services. Natural resources planners need to have at their disposal tools that can objectively help in prioritizing land use allocation. Traditional application of land use change model based on economic model, trend analysis, and or scenario analysis present some challenges of data availability and reliability necessary for implementation of the models. However, with the advent of information technology, GIS and remote sensing, biophysical data known for having influence on land use allocation can easily be accessed. The current study explores the application of GIS-Multi-criteria analysis in modeling future land use scenarios for resources planning and management using easy to construct biophysical parameters known for influencing future land use allocation. The decision problems in this study are to find the best spatial allocation of land to future agriculture and forest development, which are considered to present critical land use change in the study area. The afforestation scenarios are meant to offset the pressure on the native forest resources due to the increased demand for fuel and timber and also to contribute to the environmental protection and the agricultural land use scenarios are meant to increase productivity and ensure environmental protection. The land use scenarios did not consider “when” in the future the land use pattern may develop. The analyses of scenarios indicate that afforestation extent in the basin can be increased from 4.6% to 42.9% of the total basin area. However, the afforestation extent of 42.9% may be considered unrealistic, since in practice, it may not be possible to realize up to 42.9% afforestation, nevertheless, the spatial pattern of the afforestation may provide crucial insight into spatial afforestation policies and it future consequences. The agricultural land use can increase from 6.2% to 53.7% of the basin area. The agricultural land use expansion can be realised since the expansion of farm land is primarily the main option to achieve food production increase in the near future. The findings indicate potential use of the methodology in land use planning.
文摘The COVID-19 pandemic has a significant impact on the global economy and health.While the pandemic continues to cause casualties in millions,many countries have gone under lockdown.During this period,people have to stay within walls and become more addicted towards social networks.They express their emotions and sympathy via these online platforms.Thus,popular social media(Twitter and Facebook)have become rich sources of information for Opinion Mining and Sentiment Analysis on COVID-19-related issues.We have used Aspect Based Sentiment Analysis to anticipate the polarity of public opinion underlying different aspects from Twitter during lockdown and stepwise unlock phases.The goal of this study is to find the feelings of Indians about the lockdown initiative taken by the Government of India to stop the spread of Coronavirus.India-specific COVID-19 tweets have been annotated,for analysing the sentiment of common public.To classify the Twitter data set a deep learning model has been proposed which has achieved accuracies of 82.35%for Lockdown and 83.33%for Unlock data set.The suggested method outperforms many of the contemporary approaches(long shortterm memory,Bi-directional long short-term memory,Gated Recurrent Unit etc.).This study highlights the public sentiment on lockdown and stepwise unlocks,imposed by the Indian Government on various aspects during the Corona outburst.
