With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that consid...With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.展开更多
The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the intera...The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.展开更多
The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of...The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of a steeply dipping superimposed cantilever beam in the surrounding rock was deduced based on limit equilibrium theory.The results show the following:(1)surface displacement above metal mines with steeply dipping discontinuities shows significant step characteristics,and(2)the behavior of the strata as they fail exhibits superimposition characteristics.Generally,failure first occurs in certain superimposed strata slightly far from the goaf.Subsequently,with the constant downward excavation of the orebody,the superimposed strata become damaged both upwards away from and downwards toward the goaf.This process continues until the deep part of the steeply dipping superimposed strata forms a large-scale deep fracture plane that connects with the goaf.The deep fracture plane generally makes an angle of 12°-20°with the normal to the steeply dipping discontinuities.The effect of the constant outward transfer of strata movement due to the constant outward failure of the superimposed strata in the metal mines with steeply dipping discontinuities causes the scope of the strata movement in these mines to be larger than expected.The strata in the metal mines with steeply dipping discontinuities mainly show flexural toppling failure.However,the steeply dipping structural strata near the goaf mainly exhibit shear slipping failure,in which case the mechanical model used to describe them can be simplified by treating them as steeply dipping superimposed cantilever beams.By taking the steeply dipping superimposed cantilever beam that first experiences failure as the key stratum,the failure scope of the strata(and criteria for the stability of metal mines with steeply dipping discontinuities mined using sublevel caving)can be obtained via iterative computations from the key stratum,moving downward toward and upwards away from the goaf.展开更多
Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooper...Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.展开更多
The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media.Such novel decision schemes require the participation of many experts/decision makers/stakeholder...The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media.Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes.As a result,large-scale group decision making(LSGDM)has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic.Therefore,this paper aims at reviewing the most relevant studies about LSGDM,identifying the most profitable research trends and analyzing them from a critical point of view.To do so,the Web of Science database has been consulted by using different searches.From these results a total of 241 contributions were found and a selection process regarding language,type of contribution and actual relation with the studied topic was then carried out.The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic,such as the preference structure in which decision-makers’opinions are modeled,the group decision rules used to define the decision making process,the techniques applied to verify the quality of these models and their applications to real world problems solving.Afterwards,a critical analysis of the main limitations of the existing proposals is developed.Finally,taking into account these limitations,new research lines for LSGDM are proposed and the main challenges are stressed out.展开更多
From March 2014 to February 2015, the soil fauna community in the karst cave wetland of Maolan Nature Reserve was investigated. A total of 3,820 soil fauna was obtained, belonging to 31 orders, 11 classes, and 3 phyla...From March 2014 to February 2015, the soil fauna community in the karst cave wetland of Maolan Nature Reserve was investigated. A total of 3,820 soil fauna was obtained, belonging to 31 orders, 11 classes, and 3 phyla. The dominant groups were Araneae, Coleoptera and Hymenoptera, accounting for 48.90% of the total catch. There were 18 common groups and 10 rare groups. The diversity analysis showed that the Banzhai karst cave wetland had the largest soil fauna community diversity index and evenness index and that the Dongsai karst cave wetland had the largest number of groups and individuals. The seasonal variation of the soil fauna in the karst cave wetlands was analyzed: the number of soil fauna individuals showed a downtrend in summer, autumn, spring and winter; there were the highest number of phytophagous soil fauna, followed by predatory soil fauna and saprophagous soil fauna.展开更多
The pile group with elevated cap is widely used as foundation of offshore structures such as turbines, power transmission towers and bridge piers, and understanding its behavior under cyclic lateral loads induced by w...The pile group with elevated cap is widely used as foundation of offshore structures such as turbines, power transmission towers and bridge piers, and understanding its behavior under cyclic lateral loads induced by waves, tide water and winds, is of great importance to designing. A large-scale model test on 3×3 pile group with elevated cap subjected to cyclic lateral loads was performed in saturated silts. The preparation and implementation of the test is presented. Steel pipes with the outer diameter of 114 mm, thickness of 4.5 mm, and length of 6 m were employed as model piles. The pile group was cyclic loaded in a multi-stage sequence with the lateral displacement controlled. In addition, a single pile test was also conducted at the same site for comparison. The displacement of the pile cap, the internal forces of individual piles, and the horizontal stiffness of the pile group are presented and discussed in detail. The results indicate that the lateral cyclic loads have a greater impact on pile group than that on a single pile, and give rise to the significant plastic strain in the soil around piles. The lateral loads carried by each row of piles within the group would be redistributed with loading cycles. The lateral stiffness of the pile group decreases gradually with cycles and broadly presents three different degradation patterns in the test. Significant axial forces were measured out in some piles within the group, owing to the strong restraint provided by the cap, and finally lead to a large settlement of the pile group. These findings can be referred for foundation designing of offshore structures.展开更多
The national strategy of"Guangdong-Hong Kong-Macao Greater Bay Area"has replaced the original Pearl River Delta economic circle.As one of them,the economic development of Zhaoqing City ushered in a historic ...The national strategy of"Guangdong-Hong Kong-Macao Greater Bay Area"has replaced the original Pearl River Delta economic circle.As one of them,the economic development of Zhaoqing City ushered in a historic opportunity.Other cities in Greater Bay Area provide sufficient tourist resources for the development of Zhaoqing’s tourism industry.Under the new situation,Seven Star Cave,the leading scenic spot in Zhaoqing,should firmly grasp the national strategic dividend of the"Guangdong-Hong Kong-Macao Greater Bay Area",accelerate the transformation and upgrading,and enhance the market competitiveness.In this paper,the data are collected by nominal group technique,and are integrated into SWOT matrix for analysis.The development strategy of Zhaoqing Seven Star Cave Scenic Area is obtained by matching internal and external factors.展开更多
Large-scale cooling energy system has developed well in the past decade.However,its optimization is still a problem to be tackled due to the nonlinearity and large scale of existing systems.Reducing the scale of probl...Large-scale cooling energy system has developed well in the past decade.However,its optimization is still a problem to be tackled due to the nonlinearity and large scale of existing systems.Reducing the scale of problems without oversimplifying the actual system model is a big challenge nowadays.This paper proposes a dimension reduction-based many-objective optimization(DRMO)method to solve an accurate nonlinear model of a practical large-scale cooling energy system.In the first stage,many-objective and many-variable of the large system are pre-processed to reduce the overall scale of the optimization problem.The relationships between many objectives are analyzed to find a few representative objectives.Key control variables are extracted to reduce the dimension of variables and the number of equality constraints.In the second stage,the manyobjective group search optimization(GSO)method is used to solve the low-dimensional nonlinear model,and a Pareto-front is obtained.In the final stage,candidate solutions along the Paretofront are graded on many-objective levels of system operators.The candidate solution with the highest average utility value is selected as the best running mode.Simulations are carried out on a 619-node-614-branch cooling system,and results show the ability of the proposed method in solving large-scale system operation problems.展开更多
基金The work was supported by Humanities and Social Sciences Fund of the Ministry of Education(No.22YJA630119)the National Natural Science Foundation of China(No.71971051)Natural Science Foundation of Hebei Province(No.G2021501004).
文摘With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.
基金supported in part by the Central Government Guides Local Science and TechnologyDevelopment Funds(Grant No.YDZJSX2021A038)in part by theNational Natural Science Foundation of China under(Grant No.61806138)in part by the China University Industry-University-Research Collaborative Innovation Fund(Future Network Innovation Research and Application Project)(Grant 2021FNA04014).
文摘The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.
基金Financial support for this work was provided by the Youth Fund Program of the National Natural Science Foundation of China (No. 42002292)the General Program of the National Natural Science Foundation of China (No. 42377175)the General Program of the Hubei Provincial Natural Science Foundation, China (No. 2023AFB631)
文摘The deformation and fracture evolution mechanisms of the strata overlying mines mined using sublevel caving were studied via numerical simulations.Moreover,an expression for the normal force acting on the side face of a steeply dipping superimposed cantilever beam in the surrounding rock was deduced based on limit equilibrium theory.The results show the following:(1)surface displacement above metal mines with steeply dipping discontinuities shows significant step characteristics,and(2)the behavior of the strata as they fail exhibits superimposition characteristics.Generally,failure first occurs in certain superimposed strata slightly far from the goaf.Subsequently,with the constant downward excavation of the orebody,the superimposed strata become damaged both upwards away from and downwards toward the goaf.This process continues until the deep part of the steeply dipping superimposed strata forms a large-scale deep fracture plane that connects with the goaf.The deep fracture plane generally makes an angle of 12°-20°with the normal to the steeply dipping discontinuities.The effect of the constant outward transfer of strata movement due to the constant outward failure of the superimposed strata in the metal mines with steeply dipping discontinuities causes the scope of the strata movement in these mines to be larger than expected.The strata in the metal mines with steeply dipping discontinuities mainly show flexural toppling failure.However,the steeply dipping structural strata near the goaf mainly exhibit shear slipping failure,in which case the mechanical model used to describe them can be simplified by treating them as steeply dipping superimposed cantilever beams.By taking the steeply dipping superimposed cantilever beam that first experiences failure as the key stratum,the failure scope of the strata(and criteria for the stability of metal mines with steeply dipping discontinuities mined using sublevel caving)can be obtained via iterative computations from the key stratum,moving downward toward and upwards away from the goaf.
基金supported by the National Natural Science Foundation of China (Nos.71771156,71971145,72171158).
文摘Emergency decision-making problems usually involve many experts with different professional backgrounds and concerns,leading to non-cooperative behaviors during the consensus-reaching process.Many studies on noncooperative behavior management assumed that the maximumdegree of cooperation of experts is to totally accept the revisions suggested by the moderator,which restricted individuals with altruistic behaviors to make more contributions in the agreement-reaching process.In addition,when grouping a large group into subgroups by clustering methods,existing studies were based on the similarity of evaluation values or trust relationships among experts separately but did not consider them simultaneously.In this study,we introduce a clustering method considering the similarity of evaluation values and the trust relations of experts and then develop a consensusmodel taking into account the altruistic behaviors of experts.First,we cluster experts into subgroups by a constrained Kmeans clustering algorithm according to the opinion similarity and trust relationship of experts.Then,we calculate the weights of experts and clusters based on the centrality degrees of experts.Next,to enhance the quality of consensus reaching,we identify three kinds of non-cooperative behaviors and propose corresponding feedback mechanisms relying on the altruistic behaviors of experts.A numerical example is given to show the effectiveness and practicality of the proposed method in emergency decision-making.The study finds that integrating altruistic behavior analysis in group decision-making can safeguard the interests of experts and ensure the integrity of decision-making information.
基金supported by the Spanish Ministry of Economy and Competitiveness through the Spanish National Project PGC2018-099402-B-I00the Postdoctoral fellow Ramón y Cajal(RYC-2017-21978)+6 种基金the FEDER-UJA project 1380637ERDF,the Spanish Ministry of Science,Innovation and Universities through a Formación de Profesorado Universitario(FPU2019/01203)grantthe Junta de Andalucía,Andalusian Plan for Research,Development,and Innovation(POSTDOC 21-00461)the National Natural Science Foundation of China(61300167,61976120)the Natural Science Foundation of Jiangsu Province(BK20191445)the Natural Science Key Foundation of Jiangsu Education Department(21KJA510004)Qing Lan Project of Jiangsu Province。
文摘The society in the digital transformation era demands new decision schemes such as e-democracy or based on social media.Such novel decision schemes require the participation of many experts/decision makers/stakeholders in the decision processes.As a result,large-scale group decision making(LSGDM)has attracted the attention of many researchers in the last decade and many studies have been conducted in order to face the challenges associated with the topic.Therefore,this paper aims at reviewing the most relevant studies about LSGDM,identifying the most profitable research trends and analyzing them from a critical point of view.To do so,the Web of Science database has been consulted by using different searches.From these results a total of 241 contributions were found and a selection process regarding language,type of contribution and actual relation with the studied topic was then carried out.The 87 contributions finally selected for this review have been analyzed from four points of view that have been highly remarked in the topic,such as the preference structure in which decision-makers’opinions are modeled,the group decision rules used to define the decision making process,the techniques applied to verify the quality of these models and their applications to real world problems solving.Afterwards,a critical analysis of the main limitations of the existing proposals is developed.Finally,taking into account these limitations,new research lines for LSGDM are proposed and the main challenges are stressed out.
基金Sponsored by National Natural Science Foundation of China(31660152)Youth Program Funded by Guizhou Provincial Department of Forestry([2013]10)Guizhou Science and Technology Fund([2013]2135)
文摘From March 2014 to February 2015, the soil fauna community in the karst cave wetland of Maolan Nature Reserve was investigated. A total of 3,820 soil fauna was obtained, belonging to 31 orders, 11 classes, and 3 phyla. The dominant groups were Araneae, Coleoptera and Hymenoptera, accounting for 48.90% of the total catch. There were 18 common groups and 10 rare groups. The diversity analysis showed that the Banzhai karst cave wetland had the largest soil fauna community diversity index and evenness index and that the Dongsai karst cave wetland had the largest number of groups and individuals. The seasonal variation of the soil fauna in the karst cave wetlands was analyzed: the number of soil fauna individuals showed a downtrend in summer, autumn, spring and winter; there were the highest number of phytophagous soil fauna, followed by predatory soil fauna and saprophagous soil fauna.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51225804 and U1234204)the Zhejiang Electric Power Design Institute
文摘The pile group with elevated cap is widely used as foundation of offshore structures such as turbines, power transmission towers and bridge piers, and understanding its behavior under cyclic lateral loads induced by waves, tide water and winds, is of great importance to designing. A large-scale model test on 3×3 pile group with elevated cap subjected to cyclic lateral loads was performed in saturated silts. The preparation and implementation of the test is presented. Steel pipes with the outer diameter of 114 mm, thickness of 4.5 mm, and length of 6 m were employed as model piles. The pile group was cyclic loaded in a multi-stage sequence with the lateral displacement controlled. In addition, a single pile test was also conducted at the same site for comparison. The displacement of the pile cap, the internal forces of individual piles, and the horizontal stiffness of the pile group are presented and discussed in detail. The results indicate that the lateral cyclic loads have a greater impact on pile group than that on a single pile, and give rise to the significant plastic strain in the soil around piles. The lateral loads carried by each row of piles within the group would be redistributed with loading cycles. The lateral stiffness of the pile group decreases gradually with cycles and broadly presents three different degradation patterns in the test. Significant axial forces were measured out in some piles within the group, owing to the strong restraint provided by the cap, and finally lead to a large settlement of the pile group. These findings can be referred for foundation designing of offshore structures.
基金Supported by the Characteristic Innovation Projects of Ordinary Colleges and Universities in Guangdong Province(2018WTSCX154)。
文摘The national strategy of"Guangdong-Hong Kong-Macao Greater Bay Area"has replaced the original Pearl River Delta economic circle.As one of them,the economic development of Zhaoqing City ushered in a historic opportunity.Other cities in Greater Bay Area provide sufficient tourist resources for the development of Zhaoqing’s tourism industry.Under the new situation,Seven Star Cave,the leading scenic spot in Zhaoqing,should firmly grasp the national strategic dividend of the"Guangdong-Hong Kong-Macao Greater Bay Area",accelerate the transformation and upgrading,and enhance the market competitiveness.In this paper,the data are collected by nominal group technique,and are integrated into SWOT matrix for analysis.The development strategy of Zhaoqing Seven Star Cave Scenic Area is obtained by matching internal and external factors.
基金supported by the Key-Area Research and Development Program of Guangdong Province(2020B010166004)Natural Science Foundation of China(52007066).
文摘Large-scale cooling energy system has developed well in the past decade.However,its optimization is still a problem to be tackled due to the nonlinearity and large scale of existing systems.Reducing the scale of problems without oversimplifying the actual system model is a big challenge nowadays.This paper proposes a dimension reduction-based many-objective optimization(DRMO)method to solve an accurate nonlinear model of a practical large-scale cooling energy system.In the first stage,many-objective and many-variable of the large system are pre-processed to reduce the overall scale of the optimization problem.The relationships between many objectives are analyzed to find a few representative objectives.Key control variables are extracted to reduce the dimension of variables and the number of equality constraints.In the second stage,the manyobjective group search optimization(GSO)method is used to solve the low-dimensional nonlinear model,and a Pareto-front is obtained.In the final stage,candidate solutions along the Paretofront are graded on many-objective levels of system operators.The candidate solution with the highest average utility value is selected as the best running mode.Simulations are carried out on a 619-node-614-branch cooling system,and results show the ability of the proposed method in solving large-scale system operation problems.