Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other ...Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.展开更多
Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expa...Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expand,effective risk assessment and management have become critical.This study develops a comprehensive risk evaluation framework for China’s overseas renewable energy investments using the Fuzzy Analytic Hierarchy Process(FAHP).The framework incorporates political,economic,and project-specific risks,organized through three primary criteria,nine sub-criteria,and thirty tertiary indicators.By integrating expert judgments with fuzzy set theory,the FAHP methodology assigns accurate weights to risk factors and ensures consistency in evaluation.The findings identify political risks as the most significant,emphasizing their influence on investment strategies.These insights offer valuable guidance for policymakers and investors to enhance risk management strategies and ensure the sustainability of China’s renewable energy initiatives abroad.展开更多
A dissertation is a research report or scientific paper written by an author to obtain a certain degree. It reflects postgraduates’ research achievements and the educational quality of an institute, even a country. T...A dissertation is a research report or scientific paper written by an author to obtain a certain degree. It reflects postgraduates’ research achievements and the educational quality of an institute, even a country. To construct an optimized quality evaluation system for postgraduate dissertation (QESPD), we summarized the influencing factors and invited 10 experienced specialists to rate and prioritize them based on fuzzy analytic hierarchy process. Four primary indicators (innovation, integrity, scientificity and normativity) and 16 sub-indicators were selected to form the evaluation system. The order of primary indicators by weight, was innovation (0.4269), scientificity (0.2807), integrity (0.1728) and normativity (0.1196). The top five sub-dimensions were theoretical originality, scientific value, data reliability, design rationality and evidence credibility. To demonstrate the effectiveness of the proposed system, a case study was performed. In the case study, it was demonstrated that the established two-index-hierarchy QESPD in this study was a more scientific and reasonable evaluation system worthy of promotion and application.展开更多
Based on the perception of flood risk factors derived from the lessons learned by the main stakeholders, namely the members of the National Emergency Response Plan (ORSEC) and the people affected by floods in the stud...Based on the perception of flood risk factors derived from the lessons learned by the main stakeholders, namely the members of the National Emergency Response Plan (ORSEC) and the people affected by floods in the study area (Thies, Senegal), this work consists of modelling the flood risk using Hierarchical Process Analysis (HPA). This modelling made it possible to determine the coherence index (CI) and the coherence ratio, which were evaluated respectively at 0.27% and 5% according to the perception of the members of the ORSEC Plan, and at 0.28% and 5% according to the perception of the disaster victims. These results show that the working approach is coherent and acceptable. We then carried out Hierarchical Fuzzy Process Analysis (HFPA), an extension of HFPA, which seeks to minimize the margins of error. FPHA uses fuzzification of perception contributions, interference rules and defuzzification to determine the Net Flood Risk Index (NFRI). Integrated with ArcGIS software, the NFRI is used to generate flood risk maps that reveal a high risk of vulnerability of the main outlets occupied by human settlements.展开更多
Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deplo...Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.展开更多
Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in ne...Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.展开更多
For critical engineering systems such as aircraft and aerospace vehicles, accurate Remaining Useful Life(RUL) prediction not only means cost saving, but more importantly, is of great significance in ensuring system re...For critical engineering systems such as aircraft and aerospace vehicles, accurate Remaining Useful Life(RUL) prediction not only means cost saving, but more importantly, is of great significance in ensuring system reliability and preventing disaster. RUL is affected not only by a system's intrinsic deterioration, but also by the operational conditions under which the system is operating. This paper proposes an RUL prediction approach to estimate the mean RUL of a continuously degrading system under dynamic operational conditions and subjected to condition monitoring at short equi-distant intervals. The dynamic nature of the operational conditions is described by a discrete-time Markov chain, and their influences on the degradation signal are quantified by degradation rates and signal jumps in the degradation model. The uniqueness of our proposed approach is formulating the RUL prediction problem in a semi-Markov decision process framework, by which the system mean RUL can be obtained through the solution to a limited number of equations. To extend the use of our proposed approach in real applications, different failure standards according to different operational conditions are also considered. The application and effectiveness of this approach are illustrated by a turbofan engine dataset and a comparison with existing results for the same dataset.展开更多
For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring st...For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.展开更多
A Three-Scale Fuzzy Analytical Hierarchy Process (T-FAHP) is proposed by introducing the Three-Scale Analytical Hierarchy Process (T-AHP) and the trapezoid fuzzy number. A multi-objective optimization model based on t...A Three-Scale Fuzzy Analytical Hierarchy Process (T-FAHP) is proposed by introducing the Three-Scale Analytical Hierarchy Process (T-AHP) and the trapezoid fuzzy number. A multi-objective optimization model based on the T-FAHP is presented subsequently, in which many factors influencing the lectotype of offshore platform are taken into account synthetically, such as the original investment, the maintenance, cost, the ability of resisting fatigue and corrosion, the construction period, the threat to the environment, and so on. With this method, the experts can give the relatively precise ranking weight of each index and at the same time the requirement of consistence checking can be met, The result of a calculation example shows that the T-FAHP is practical.展开更多
In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(...In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.展开更多
Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information a...Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.展开更多
Casing corrosion during CO2 injection or storage results in significant economic loss and increased production risks.Therefore,in this paper,a corroded casing risk assessment model based on analytic hierarchy process ...Casing corrosion during CO2 injection or storage results in significant economic loss and increased production risks.Therefore,in this paper,a corroded casing risk assessment model based on analytic hierarchy process and fuzzy comprehensive evaluation is established to identify potential risks in time.First,the corrosion rate and residual strength characteristics are analyzed through corrosion tests and numerical simulations,respectively,to determine the risk factors that may lead to an accident.Then,an index system for corroded casing risk evaluation is established based on six important factors:temperature,CO2 partial pressure,flow velocity,corrosion radius,corrosion depth and wellhead pressure.Subsequently,the index weights are calculated via the analytic hierarchy process.Finally,the risk level of corroded casing is obtained via the fuzzy comprehensive evaluation.The corroded casing risk assessment model has been verified by a case well,which shows that the model is valuable and feasible.It provides an effective decision-making method for the risk evaluation of corroded casing in CO2 injection well,which is conductive to improve the wellbore operation efficiency.展开更多
Nitrogen and phosphorous concentrations of effluent water must be taken into account for the design and operation of wastewater treatment plants. In addition, the requirement for effluent quality is becoming strict. T...Nitrogen and phosphorous concentrations of effluent water must be taken into account for the design and operation of wastewater treatment plants. In addition, the requirement for effluent quality is becoming strict. Therefore, intelligent control approaches are recently required in removing biological nutrient. In this study, fuzzy control has been successfully applied to improve the nitrogen removal. Experimental results showed that a close relationship between nitrate concentration and oxidation-reduction potential (ORP) at the end of anoxic zone was found for anoxic/oxic (A/O) nitrogen removal process treating synthetic wastewater. ORP can be used as online fuzzy control parameter of nitrate recirculation and external carbon addition. The established fuzzy logic controller that includes two inputs and one output can maintain ORP value at - 86 mV and - 90 mV by adjusting the nitrate recirculation flow and external carbon dosage respectively to realize the optimal control of nitrogen removal, improving the effluent quality and reducing the operating cost.展开更多
Stamping process,which is widely used in automobile,aerospace,machine-building industries,and etc.,is a creative process needing time and experiences.The lead time is mainly spent on stamping die design and manufactur...Stamping process,which is widely used in automobile,aerospace,machine-building industries,and etc.,is a creative process needing time and experiences.The lead time is mainly spent on stamping die design and manufacturing.As the ba- sis of die design,process design is a non-linearity and creative process,which can be solved by using the fuzzy synthetic evaluation. In this paper,the potential o f fuzzy synthetic evaluation for dealing with stamping process design was explored.The influencing factor set,factor weight set,evaluation set,single factor fuzzy evaluation matrix,and fuzzy synthetic evaluation scheme were studied.Finally,the washer part,considering forming equipment,part dimensions and other factors,was selected to testify the evaluation process.展开更多
As a difficult problem, sidewall instability has been beset drilling workers all the time. Not only does it cause huge economic losses, but also it determines the success or failure of drilling engineering. Due to com...As a difficult problem, sidewall instability has been beset drilling workers all the time. Not only does it cause huge economic losses, but also it determines the success or failure of drilling engineering. Due to complex relationship between various factors which influence sidewall stability, it hasn’t been found a widely applied method to predicate sidewall stability so far. Therefore, in order to formulate corresponding measures to ensure successful drilling, searching for a kind of better method to forecast sidewall stability before drilling becomes an imperative and significant topic for drilling engineering. On the basis of traditional sidewall stability analytical method, we have put forward the Fuzzy Comprehensive Evaluation Method to forecast sidewall stability regulation using physico-chemical performance parameters of the clay mineral. This method has been improved by introducing the Analytic Hierarchy Process (AHP) and the Maximum Subjection Principle in the application process. After introducing Analytic Hierarchy Process to identify weight, and Maximum Subjection Principle to obtain evaluation results, it has reduced the influence of human factors and enhanced the accuracy of the fuzzy evaluation results. The application in Hailaer Area indicates that this method can predict sidewall stability of gas-oil well with high credibility and strong practicability.展开更多
Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually sin...Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construction sites due to lack of risk management ability. The need to prevent losses at nuclear power plant construction sites has become more urgent because it demands professional skills and large-scale resources. Therefore, in this study, the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) were applied in order to make comparisons between decision-making methods, to assess the potential risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment using the AHP. These risk factors will be able to serve as baseline data for risk management in nuclear power plant construction projects.展开更多
文摘Drought conditions at a given location evolve randomly through time and are typically characterized by severity and duration. Researchers interested in modeling the economic effects of drought on agriculture or other water users often capture the stochastic nature of drought and its conditions via multiyear, stochastic economic models. Three major sources of uncertainty in application of a multiyear discrete stochastic model to evaluate user preparedness and response to drought are: (1) the assumption of independence of yearly weather conditions, (2) linguistic vagueness in the definition of drought itself, and (3) the duration of drought. One means of addressing these uncertainties is to re-cast drought as a stochastic, multiyear process using a “fuzzy” semi-Markov process. In this paper, we review “crisp” versus “fuzzy” representations of drought and show how fuzzy semi-Markov processes can aid researchers in developing more robust multiyear, discrete stochastic models.
基金supported by the project VSB-TU Ostrava,SP2024/045.
文摘Renewable energy sources,including wind,solar,and biofuels,are essential for promoting sustainable economic development and mitigating environmental challenges.As China’s overseas investments in renewable energy expand,effective risk assessment and management have become critical.This study develops a comprehensive risk evaluation framework for China’s overseas renewable energy investments using the Fuzzy Analytic Hierarchy Process(FAHP).The framework incorporates political,economic,and project-specific risks,organized through three primary criteria,nine sub-criteria,and thirty tertiary indicators.By integrating expert judgments with fuzzy set theory,the FAHP methodology assigns accurate weights to risk factors and ensures consistency in evaluation.The findings identify political risks as the most significant,emphasizing their influence on investment strategies.These insights offer valuable guidance for policymakers and investors to enhance risk management strategies and ensure the sustainability of China’s renewable energy initiatives abroad.
文摘A dissertation is a research report or scientific paper written by an author to obtain a certain degree. It reflects postgraduates’ research achievements and the educational quality of an institute, even a country. To construct an optimized quality evaluation system for postgraduate dissertation (QESPD), we summarized the influencing factors and invited 10 experienced specialists to rate and prioritize them based on fuzzy analytic hierarchy process. Four primary indicators (innovation, integrity, scientificity and normativity) and 16 sub-indicators were selected to form the evaluation system. The order of primary indicators by weight, was innovation (0.4269), scientificity (0.2807), integrity (0.1728) and normativity (0.1196). The top five sub-dimensions were theoretical originality, scientific value, data reliability, design rationality and evidence credibility. To demonstrate the effectiveness of the proposed system, a case study was performed. In the case study, it was demonstrated that the established two-index-hierarchy QESPD in this study was a more scientific and reasonable evaluation system worthy of promotion and application.
文摘Based on the perception of flood risk factors derived from the lessons learned by the main stakeholders, namely the members of the National Emergency Response Plan (ORSEC) and the people affected by floods in the study area (Thies, Senegal), this work consists of modelling the flood risk using Hierarchical Process Analysis (HPA). This modelling made it possible to determine the coherence index (CI) and the coherence ratio, which were evaluated respectively at 0.27% and 5% according to the perception of the members of the ORSEC Plan, and at 0.28% and 5% according to the perception of the disaster victims. These results show that the working approach is coherent and acceptable. We then carried out Hierarchical Fuzzy Process Analysis (HFPA), an extension of HFPA, which seeks to minimize the margins of error. FPHA uses fuzzification of perception contributions, interference rules and defuzzification to determine the Net Flood Risk Index (NFRI). Integrated with ArcGIS software, the NFRI is used to generate flood risk maps that reveal a high risk of vulnerability of the main outlets occupied by human settlements.
文摘Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.
基金funded by Ongoing Research Funding program(ORF-2025-749),King Saud University,Riyadh,Saudi Arabia.
文摘Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.
基金the National Natural science Foundation of China (No. 71701008) for supporting this research
文摘For critical engineering systems such as aircraft and aerospace vehicles, accurate Remaining Useful Life(RUL) prediction not only means cost saving, but more importantly, is of great significance in ensuring system reliability and preventing disaster. RUL is affected not only by a system's intrinsic deterioration, but also by the operational conditions under which the system is operating. This paper proposes an RUL prediction approach to estimate the mean RUL of a continuously degrading system under dynamic operational conditions and subjected to condition monitoring at short equi-distant intervals. The dynamic nature of the operational conditions is described by a discrete-time Markov chain, and their influences on the degradation signal are quantified by degradation rates and signal jumps in the degradation model. The uniqueness of our proposed approach is formulating the RUL prediction problem in a semi-Markov decision process framework, by which the system mean RUL can be obtained through the solution to a limited number of equations. To extend the use of our proposed approach in real applications, different failure standards according to different operational conditions are also considered. The application and effectiveness of this approach are illustrated by a turbofan engine dataset and a comparison with existing results for the same dataset.
基金Supported by the National Natural Science Foundation of China (61074079)Shanghai Leading Academic Discipline Project (B054)
文摘For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.59895410)
文摘A Three-Scale Fuzzy Analytical Hierarchy Process (T-FAHP) is proposed by introducing the Three-Scale Analytical Hierarchy Process (T-AHP) and the trapezoid fuzzy number. A multi-objective optimization model based on the T-FAHP is presented subsequently, in which many factors influencing the lectotype of offshore platform are taken into account synthetically, such as the original investment, the maintenance, cost, the ability of resisting fatigue and corrosion, the construction period, the threat to the environment, and so on. With this method, the experts can give the relatively precise ranking weight of each index and at the same time the requirement of consistence checking can be met, The result of a calculation example shows that the T-FAHP is practical.
基金Project(50977003) supported by the National Natural Science Foundation of China
文摘In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.
基金Partially supported by the National Natural Science Foundation of China (No. 29976003), the Key Research Project ofScience and Technology from Ministry of Education in China (No. 01024), and Sinopec Science & Technology DevelopmentProject (No. E03007)
文摘Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process.
基金This work was supported by the National Natural Science Foundation of China(Grant No.2016ZX05042004)the Joint Funds of the National Natural Science Foundation of China(Grant no.U1762104)+3 种基金the Major Scientific and Technological Projects of CNPC(Grant No.ZD2019-184-004)the Fundamental Research Funds for the Central Universities(20CX02306A)the Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration EquipmentThe authors also would like to express their sincere gratitude to Dr.Zhang Dalei for his assistance in corrosion tests.
文摘Casing corrosion during CO2 injection or storage results in significant economic loss and increased production risks.Therefore,in this paper,a corroded casing risk assessment model based on analytic hierarchy process and fuzzy comprehensive evaluation is established to identify potential risks in time.First,the corrosion rate and residual strength characteristics are analyzed through corrosion tests and numerical simulations,respectively,to determine the risk factors that may lead to an accident.Then,an index system for corroded casing risk evaluation is established based on six important factors:temperature,CO2 partial pressure,flow velocity,corrosion radius,corrosion depth and wellhead pressure.Subsequently,the index weights are calculated via the analytic hierarchy process.Finally,the risk level of corroded casing is obtained via the fuzzy comprehensive evaluation.The corroded casing risk assessment model has been verified by a case well,which shows that the model is valuable and feasible.It provides an effective decision-making method for the risk evaluation of corroded casing in CO2 injection well,which is conductive to improve the wellbore operation efficiency.
基金Supported by the Key International Cooperation Project of NSFC, Key Project of NSFC (No. 50138010)863 Hi-Technology Research and Development Program of China (2003AA601010).
文摘Nitrogen and phosphorous concentrations of effluent water must be taken into account for the design and operation of wastewater treatment plants. In addition, the requirement for effluent quality is becoming strict. Therefore, intelligent control approaches are recently required in removing biological nutrient. In this study, fuzzy control has been successfully applied to improve the nitrogen removal. Experimental results showed that a close relationship between nitrate concentration and oxidation-reduction potential (ORP) at the end of anoxic zone was found for anoxic/oxic (A/O) nitrogen removal process treating synthetic wastewater. ORP can be used as online fuzzy control parameter of nitrate recirculation and external carbon addition. The established fuzzy logic controller that includes two inputs and one output can maintain ORP value at - 86 mV and - 90 mV by adjusting the nitrate recirculation flow and external carbon dosage respectively to realize the optimal control of nitrogen removal, improving the effluent quality and reducing the operating cost.
文摘Stamping process,which is widely used in automobile,aerospace,machine-building industries,and etc.,is a creative process needing time and experiences.The lead time is mainly spent on stamping die design and manufacturing.As the ba- sis of die design,process design is a non-linearity and creative process,which can be solved by using the fuzzy synthetic evaluation. In this paper,the potential o f fuzzy synthetic evaluation for dealing with stamping process design was explored.The influencing factor set,factor weight set,evaluation set,single factor fuzzy evaluation matrix,and fuzzy synthetic evaluation scheme were studied.Finally,the washer part,considering forming equipment,part dimensions and other factors,was selected to testify the evaluation process.
文摘As a difficult problem, sidewall instability has been beset drilling workers all the time. Not only does it cause huge economic losses, but also it determines the success or failure of drilling engineering. Due to complex relationship between various factors which influence sidewall stability, it hasn’t been found a widely applied method to predicate sidewall stability so far. Therefore, in order to formulate corresponding measures to ensure successful drilling, searching for a kind of better method to forecast sidewall stability before drilling becomes an imperative and significant topic for drilling engineering. On the basis of traditional sidewall stability analytical method, we have put forward the Fuzzy Comprehensive Evaluation Method to forecast sidewall stability regulation using physico-chemical performance parameters of the clay mineral. This method has been improved by introducing the Analytic Hierarchy Process (AHP) and the Maximum Subjection Principle in the application process. After introducing Analytic Hierarchy Process to identify weight, and Maximum Subjection Principle to obtain evaluation results, it has reduced the influence of human factors and enhanced the accuracy of the fuzzy evaluation results. The application in Hailaer Area indicates that this method can predict sidewall stability of gas-oil well with high credibility and strong practicability.
文摘Recently, plant construction throughout the world, including nuclear power plant construction, has grown significantly. The scale of Korea’s nuclear power plant construction in particular, has increased gradually since it won a contract for a nuclear power plant construction project in the United Arab Emirates in 2009. However, time and monetary resources have been lost in some nuclear power plant construction sites due to lack of risk management ability. The need to prevent losses at nuclear power plant construction sites has become more urgent because it demands professional skills and large-scale resources. Therefore, in this study, the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) were applied in order to make comparisons between decision-making methods, to assess the potential risks at nuclear power plant construction sites. To suggest the appropriate choice between two decision-making methods, a survey was carried out. From the results, the importance and the priority of 24 risk factors, classified by process, cost, safety, and quality, were analyzed. The FAHP was identified as a suitable method for risk assessment of nuclear power plant construction, compared with risk assessment using the AHP. These risk factors will be able to serve as baseline data for risk management in nuclear power plant construction projects.
