Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a fr...Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attr...An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. An eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. Two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an MADM problem. The simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. Finally, a numerical example is given to show the feasibility and effectiveness of the method. The result shows that it is easier than other methods of integrating subjective and objective information.展开更多
In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternati...In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.展开更多
To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation...To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.展开更多
With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medici...With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.展开更多
Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application,it is necessary to adopt different forms of information expression according to the actual situation o...Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application,it is necessary to adopt different forms of information expression according to the actual situation of specific decision-making problems and choose the best method to solve them.Multi-valued neutrosophic set,as an extension of neutrosophic set,can more effectively and accurately describe incomplete,uncertain or inconsistent information.TODIM and TOPSIS methods are two commonly used multi-attribute decision-making methods,each of which has its advantages and disadvantages.This paper proposes a new method based on TODIM and TOPSIS to solve multi-attribute decision-making problems under multi-valued neutrosophic environment.After introducing the related theory of multi-valued neutrosophic set and the traditional TODIM and TOPSIS methods,the new method based on a combination of TODIM and TOPSIS methods is described.And then,two illustrative examples proved the feasibility and validity of the proposed method.Finally,the result has been compared with some existing methods under the same examples and the proposed method’s superiority has been proved.This paper studies this kind of decision-making problem from algorithm idea,algorithm steps and decision-making influencing factors.展开更多
An approach is presented to deal with a multi-attribute decision-making problem in which the attribute weights are unknown and the attribute values take the form of uncertain linguistic variables. First, a linguistic ...An approach is presented to deal with a multi-attribute decision-making problem in which the attribute weights are unknown and the attribute values take the form of uncertain linguistic variables. First, a linguistic assessment standard is set up to deal with the uncertain linguistic attributes, and the operation laws of uncertain linguistic variables and the uncertain linguistic weighting average(ULWA)operator are introduced. Then a ranking formula of uncertain linguistic variables based on expectation-variance is proposed. As for the case without weight information, a goal program based on a warp function is constructed to determine the attribute weights, and the ULWA operator is utilized to aggregate the assessment information of uncertain linguistic variables, and the corresponding alternatives are ranked by a formula based on expectation-variance. Finally, a numerical example is given, and the results demonstrate that it is much easier and faster for the ranking method based on expectation-variance when compared to the existing methods.展开更多
In view of the uncertainty of the monitored performance parameters of aeroengines, the fluctuating scope of the monitored infurmation during a period is taken as interval numbers, and the interval multi-attribute deci...In view of the uncertainty of the monitored performance parameters of aeroengines, the fluctuating scope of the monitored infurmation during a period is taken as interval numbers, and the interval multi-attribute decision-making method is employed to predict the performance of aeroengine, The synthetic weights of interval numbers are obtained by calculating deviation degree and possibility degree. As an example of application, 5 performance parameters monitored on 10 CF6 aeroengines of China Eastern Airlines Co., Ltd are adopted as decision attributes to verify the algorithm. The obtained synthetic ranking result shows the effectiveness and rationality of the proposed method in reflecting the performance stares of aeroengins.展开更多
In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction...In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.展开更多
Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluatio...Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.展开更多
Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc es...Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.展开更多
With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental qua...With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.展开更多
Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making i...Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.展开更多
Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship am...Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.展开更多
Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient respo...Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.展开更多
The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the ...The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.展开更多
Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making sys...Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions.By considering the village spatial layout and terrain factors,a decision tree model of residential density and terrain type was constructed with accuracies of 76.47%and 96.00%,respectively.Combined with binary classification probability unit regression,an appropriate sewage treatment mode for the village was determined with 87.00%accuracy.The Analytic Hierarchy Process(AHP),combined with the Technique for Order Preference(TOPSIS)by Similarity to an Ideal Solution model,formed the basis for optimal treatment process selection under different emission standards.Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region,focusing on the standard effluent effect(0.3773),low investment cost(0.3196),and high standard effluent effect(0.5115)to determine the best treatment process for the same emission standard under different needs.The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated.This model matches village density,geographic feature,and social development level,and provides scientific support and a theoretical basis for rural sewage treatment decision-making.展开更多
Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their...Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.展开更多
文摘Background:Despite the promise shown by large language models(LLMs)for standardized tasks,their multidimensional performance in real-world oncology decision-making remains unevaluated.This study aims to introduce a framework for evaluating LLMs and physician decisions in challenging lung cancer cases.Methods:We curated 50 challenging lung cancer cases(25 local and 25 published)classified as complex,rare,or refractory.Blinded three-dimensional,five-point Likert evaluations(1–5 for comprehensiveness,specificity,and readability)compared standalone LLMs(DeepSeek R1,Claude 3.5,Gemini 1.5,and GPT-4o),physicians by experience level(junior,intermediate,and senior),and AI-assisted juniors;intergroup differences and augmentation effects were analyzed statistically.Results:Of 50 challenging cases(18 complex,17 rare,and 15 refractory)rated by three experts,DeepSeek R1 achieved scores of 3.95±0.33,3.71±0.53,and 4.26±0.18 for comprehensiveness,specificity,and readability,respectively,positioning it between intermediate(3.68,3.68,3.75)and senior(4.50,4.64,4.53)physicians.GPT-4o and Claude 3.5 reached intermediate physician–level comprehensiveness(3.76±0.39,3.60±0.39)but junior-to-intermediate physician–level specificity(3.39±0.39,3.39±0.49).All LLMs scored higher on rare cases than intermediate physicians but fell below junior physicians in refractory-case specificity.AIassisted junior physicians showed marked gains in rare cases,with comprehensiveness rising from 2.32 to 4.29(84.8%),specificity from 2.24 to 4.26(90.8%),and readability from 2.76 to 4.59(66.0%),while specificity declined by 3.2%(3.17 to 3.07)in refractory cases.Error analysis showed complementary strengths,with physicians demonstrating reasoning stability and LLMs excelling in knowledge updating and risk management.Conclusions:LLMs performed variably in clinical decision-making tasks depending on case type,performing better in rare cases and worse in refractory cases requiring longitudinal reasoning.Complementary strengths between LLMs and physicians support case-and task-tailored human–AI collaboration.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
文摘An integrated approach is proposed to investigate the fuzzy multi-attribute decision-making （MADM） problems, where subjective preferences are expressed by a pairwise comparison matrix on the relative weights of attributes and objective information is expressed by a decision matrix. An eigenvector method integrated the subjective fuzzy preference matrix and objective information is proposed. Two linear programming models based on subjective and objective information are introduced to assess the relative importance weights of attributes in an MADM problem. The simple additive weighting method is utilized to aggregate the decision information, and then all the alternatives are ranked. Finally, a numerical example is given to show the feasibility and effectiveness of the method. The result shows that it is easier than other methods of integrating subjective and objective information.
文摘In presented fuzzy multi-attribute decision-making （FMADM） problems, the information about attribute weights is interval numbers and the decision maker （DM） has fuzzy complementary preference relation on alternatives. Firstly, the decision-making information based on the subjective preference information in the form of the fuzzy complementary judgment matrix is uniform by using a translation function. Then an objective programming model is established. Attribute weights are obtained by solving the model, thus the fuzzy overall values of alternatives are derived by using the additive weighting method. Secondly, the ranking approach of alternatives is proposed based on the degree of similarity between the fuzzy positive ideal solution of alternatives （FPISA） and the fuzzy overall values. The method can sufficiently utilize the objective information of alternatives and meet the subjective requirements of the DM as much as possible. It is easy to be operated and implemented on a computer. Finally, the proposed method is applied to the project evaluation in the venture investment.
基金supported by the Research Innovation Project of Shanghai Education Committee (08YS19)the Excellent Young Teacher Project of Shanghai University
文摘To solve the uncertain multi-attribute group decision-making of unknown attribute weights,three optimal models are built to decide the corresponding ideal solution weights,standard deviation weights and mean deviation weights.The comprehensive attribute weights are gotten through the product of the above three kinds of weights.And each decision maker＇s weighted decision matrices are also received by using the integrated attribute weights.The closeness degrees are also gotten by use of technique for order preference by similarity to ideal solution（TOPSIS） through dealing with the weighted decision matrices.At the same time the group decision matrix and weighted group decision matrix are gotten by using each decision-maker＇s closeness degree to every project.Then the vertical TOPSIS method is used to calculate the closeness degree of each project.So these projects can be ranked according to their values of the closeness degree.The process of the method is also given step by step.Finally,a numerical example demonstrates the feasibility and effectiveness of the approach.
基金supported by the National Natural Science Foundation of China(Grant 62293545)Shenzhen Science and Technology Program(Grant ZDSYS20220323112000001).
文摘With the rapid development of large AI models,large decision models have further broken through the limits of human cognition and promoted the innovation of decision-making paradigms in extensive fields such as medicine and transportation.In this paper,we systematically expound on the intelligent decision-making technology and prospects driven by large AI models.Specifically,we first review the development of large AI models in recent years.Then,from the perspective of methods,we introduce important theories and technologies of large decision models,such as model architecture and model adaptation.Next,from the perspective of applications,we introduce the cutting-edge applications of large decision models in various fields,such as autonomous driving and knowledge decision-making.Finally,we discuss existing challenges,such as security issues,decision bias and hallucination phenomenon as well as future prospects,from both technology development and domain applications.We hope this review paper can help researchers understand the important progress of intelligent decision-making driven by large AI models.
基金This research was funded by the Humanities and Social Sciences Foundation of Ministry of Education of the Peoples Republic of China(17YJA630115)The recipient of the founding is DX.
文摘Due to the complexity of decision-making problems and the subjectivity of decision-makers in practical application,it is necessary to adopt different forms of information expression according to the actual situation of specific decision-making problems and choose the best method to solve them.Multi-valued neutrosophic set,as an extension of neutrosophic set,can more effectively and accurately describe incomplete,uncertain or inconsistent information.TODIM and TOPSIS methods are two commonly used multi-attribute decision-making methods,each of which has its advantages and disadvantages.This paper proposes a new method based on TODIM and TOPSIS to solve multi-attribute decision-making problems under multi-valued neutrosophic environment.After introducing the related theory of multi-valued neutrosophic set and the traditional TODIM and TOPSIS methods,the new method based on a combination of TODIM and TOPSIS methods is described.And then,two illustrative examples proved the feasibility and validity of the proposed method.Finally,the result has been compared with some existing methods under the same examples and the proposed method’s superiority has been proved.This paper studies this kind of decision-making problem from algorithm idea,algorithm steps and decision-making influencing factors.
基金The National Natural Science Foundation of China(No.70671017)
文摘An approach is presented to deal with a multi-attribute decision-making problem in which the attribute weights are unknown and the attribute values take the form of uncertain linguistic variables. First, a linguistic assessment standard is set up to deal with the uncertain linguistic attributes, and the operation laws of uncertain linguistic variables and the uncertain linguistic weighting average(ULWA)operator are introduced. Then a ranking formula of uncertain linguistic variables based on expectation-variance is proposed. As for the case without weight information, a goal program based on a warp function is constructed to determine the attribute weights, and the ULWA operator is utilized to aggregate the assessment information of uncertain linguistic variables, and the corresponding alternatives are ranked by a formula based on expectation-variance. Finally, a numerical example is given, and the results demonstrate that it is much easier and faster for the ranking method based on expectation-variance when compared to the existing methods.
文摘In view of the uncertainty of the monitored performance parameters of aeroengines, the fluctuating scope of the monitored infurmation during a period is taken as interval numbers, and the interval multi-attribute decision-making method is employed to predict the performance of aeroengine, The synthetic weights of interval numbers are obtained by calculating deviation degree and possibility degree. As an example of application, 5 performance parameters monitored on 10 CF6 aeroengines of China Eastern Airlines Co., Ltd are adopted as decision attributes to verify the algorithm. The obtained synthetic ranking result shows the effectiveness and rationality of the proposed method in reflecting the performance stares of aeroengins.
基金The Planning Program of Science and Technology of Ministry of Housing and Urban-Rural Development of China (No. 2010-K5-16)
文摘In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.
基金Supported by the Science and Technology Support Key Project of Jiangsu Province (DE2008365)~~
文摘Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.
文摘Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.
基金Shanghai Leading Academic Discipline Project (T0502)Shanghai Municipal Educational Commission Project (05EZ32).
文摘With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.
基金supported by National Basic Research Program (973 Program,No.2004CB719402)National Natural Science Foundation of China (No.60736019)Natural Science Foundation of Zhejiang Province, China(No.Y105430).
文摘Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.
基金the National Natural Science Foundation of China(71871121).
文摘Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.
文摘Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.
文摘The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.
基金supported by the Central Government Guiding Local Science and Technology Development Fund Project(No.2024SZY0343)the Joint Research Program for Ecological Conservation and High Quality Development of the Yellow River Basin(No.2022-YRUC-01-050205)+2 种基金the Higher Education Scientific Research Project of Inner Mongolia Autonomous Region(No.NJZZ23078)the project of Inner Mongolia"Prairie Talents"Engineering Innovation Entrepreneurship Talent Team,the Major Projects of Erdos Science and Technology(No.2022EEDSKJZDZX015)the Innovation Team of the Inner Mongolia Academy of Science and Technology(No.CXTD2023-01-016).
文摘Rural domestic sewage treatment is critical for environmental protection.This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions.By considering the village spatial layout and terrain factors,a decision tree model of residential density and terrain type was constructed with accuracies of 76.47%and 96.00%,respectively.Combined with binary classification probability unit regression,an appropriate sewage treatment mode for the village was determined with 87.00%accuracy.The Analytic Hierarchy Process(AHP),combined with the Technique for Order Preference(TOPSIS)by Similarity to an Ideal Solution model,formed the basis for optimal treatment process selection under different emission standards.Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region,focusing on the standard effluent effect(0.3773),low investment cost(0.3196),and high standard effluent effect(0.5115)to determine the best treatment process for the same emission standard under different needs.The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated.This model matches village density,geographic feature,and social development level,and provides scientific support and a theoretical basis for rural sewage treatment decision-making.
基金This study has received funding by the Science and Technology Plan Project of Keqiao District(No.2020KZ58).
文摘Since existing selection methods of surgical treatment schemes of renal cancer patients mainly depend on physicians’clinical experience and judgments,the surgical treatment options of renal cancer patients lack their scientifical and reasonable information expression and group decision-making model for renal cancer patients.Fuzzy multi-sets(FMSs)have a number of properties,which make them suitable for expressing the uncertain information of medical diagnoses and treatments in group decision-making(GDM)problems.To choose the most appropriate surgical treatment scheme for a patient with localized renal cell carcinoma(RCC)(T1 stage kidney tumor),this article needs to develop an effective GDM model based on the fuzzy multivalued evaluation information of the renal cancer patients.First,we propose a conversionmethod of transforming FMSs into entropy fuzzy sets(EFSs)based on the mean and Shannon entropy of a fuzzy sequence in FMS to reasonably simplify the information expression and operations of FMSs and define the score function of an entropy fuzzy element(EFE)for ranking EFEs.Second,we present the Aczel-Alsina t-norm and t-conorm operations of EFEs and the EFE Aczel-Alsina weighted arithmetic averaging(EFEAAWAA)and EFE Aczel-Alsina weighted geometric averaging(EFEAAWGA)operators.Third,we develop a multicriteria GDM model of renal cancer surgery options in the setting of FMSs.Finally,the proposed GDM model is applied to two clinical cases of renal cancer patients to choose the best surgical treatment scheme for a renal cancer patient in the setting of FMSs.The selected results of two clinical cases verify the efficiency and rationality of the proposed GDM model in the setting of FMSs.
