2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)最新文献_第6页

A System Methodology Used for Urban Traffic Condition Estimation 城市交通状况估计的系统方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.58

Chen Zhang, Jie He, Wen Hang, Chihang Zhao

引用次数: 0

Meta-heuristics to Optimise Complex FIFO (Fly-in-Fly-out) Workforce Roster Modelling in the Mining Sector 优化采矿部门复杂FIFO(飞进飞出)劳动力名册模型的元启发式方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.93

Luke Bermingham, Kyungmi Lee, Trina S. Myers

引用次数: 0

A Traffic Signal Co-learning Adaptive Control Method Based on Gridding Model and Probability Grey Number Theory 基于网格模型和概率灰数理论的交通信号共同学习自适应控制方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.106

Junping Xiang, Zonghai Chen

{"title":"A Traffic Signal Co-learning Adaptive Control Method Based on Gridding Model and Probability Grey Number Theory","authors":"Junping Xiang, Zonghai Chen","doi":"10.1109/ISKE.2015.106","DOIUrl":"https://doi.org/10.1109/ISKE.2015.106","url":null,"abstract":"The increasing volume of traffic in cities has a significant effect on the road traffic congestions and as well the time it takes for road users to reach their destination. In this paper, we use the information of vehicles on the road network, including position, velocity, number of passengers, destination etc., as system inputs, to establish adaptive traffic signal coordination optimization model, in order to generate the optimal traffic signal area coordinated control scheme, and to suggest the best route to vehicles dynamically. We divide road network into grids, and use Mix-truncation-gauss-probabilitybased Interval Grey Number to describe vehicle position. The target of system optimization is to minimize the Total Trip Travel Time. To solve the problem, dynamic programming model is established, and the iterative algorithm is presented. A nice feature of our method is to recommend the shortest paths for vehicles when optimizing signal timing scheme of each intersection, which is called co-learning. Simulation results show that, the proposed method outperforms the Fixtiming method and Vehicle Actuated method on multiple evaluation indexes, including the Average Vehicle Delay Time, Average Vehicle Queue Length, Stops, Total Trip Travel Time and so on.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125084294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decision Making Approaches Based on Type 2 Fuzzy Soft Sets 基于二类模糊软集的决策方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.65

Yaya Liu, K. Qin, Yang Xu

引用次数: 0

An Automatic Mapping Mechanism for Formalizing Domain-Specific Metamodels 用于形式化领域特定元模型的自动映射机制

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.26

Tao Jiang, Xin Wang, Lidong Huang

引用次数: 1

MOCEO: A Proposal for Multiple Objective Cross-Entropy Optimization Method MOCEO:一种多目标交叉熵优化方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.76

Duo Zhao, Wei-dong Jin

{"title":"MOCEO: A Proposal for Multiple Objective Cross-Entropy Optimization Method","authors":"Duo Zhao, Wei-dong Jin","doi":"10.1109/ISKE.2015.76","DOIUrl":"https://doi.org/10.1109/ISKE.2015.76","url":null,"abstract":"We provide a novel Cross-Entropy optimization approach solving multi-objective optimization problems, that is called Multi-Objective Cross-Entropy Optimization (MOCEO) in recent article. The Cross-Entropy (CE) method belongs to one kind of the stochastic learning algorithm, which is inspired from the rare event simulation problems, and is proved to be successful and converge quickly in the case of single objective otimization problems. Our study modifies the basic CE method and extends the application of the algorithm for solving multi-objective optimization problems. A new parameter updating mechanism is used in MOCEO, and a recombination operator is implemented in MOCEO to enhance the algorithm's global search ability. In order to maintain the diversity of the population and to improve the computational efficiency, two truncation mechanisms for individual selection are applied in the algorithm. MOCEO has been evaluated on some standard multi-objective optimization test problems and the performance assessed by using different performance metrics. Comparing to some well-known multi-objective evolutionary algorithms and with recently proposed multi-objective Cross-Entropy algorithms, the simulation results demonstrate that the MOCEO is an effective algorithm for solving multi-object optimization problems.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125223874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Control Method to Avoid Obstacles for an Intelligent Car Based on Rough Sets and Neighborhood Systems 基于粗糙集和邻域系统的智能汽车避障控制方法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.61

Yi Jiang, Hailiang Zhao, Huimin Fu

引用次数: 5

Expansible Computable Aggregation Rules 可扩展的可计算聚合规则

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.95

L. Garmendia, Ramón González del Campo, J. Montero

引用次数: 2

A Compromise-Based Particle Swarm Optimization Algorithm for Solving Bi-Level Programming Problems with Fuzzy Parameters 基于妥协的粒子群优化算法求解模糊参数双层规划问题

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.21

Jialin Han, Yaoguang Hu, Guangquan Zhang, Jie Lu

引用次数: 0

A Consensus Model for Group Decision Making with Hesitant Fuzzy Linguistic Information 带有犹豫模糊语言信息的群体决策共识模型

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2015-11-01 DOI: 10.1109/ISKE.2015.31

Rosa M. Rodríguez, L. Martínez

{"title":"A Consensus Model for Group Decision Making with Hesitant Fuzzy Linguistic Information","authors":"Rosa M. Rodríguez, L. Martínez","doi":"10.1109/ISKE.2015.31","DOIUrl":"https://doi.org/10.1109/ISKE.2015.31","url":null,"abstract":"Group Decision Making (GDM) is a usual process in companies and administration in which complex decision problems are solved taking into account different points of view from different experts involved in the decision situation. Notwithstanding, in principle group decisions should be better accepted than decisions made by a single decision maker because they try to include several viewpoints, sometimes the decision processes do not consider the agreement in the solution, therefore such solutions can fail in their goal. To overcome such a problem, a consensus reaching process is added to GDM processes to obtain solutions with a high degree of agreement. The complexity of GDM problems are often due to the uncertainty related to the imprecision and vagueness of the meaning of the decision situation that is modelled by linguistic descriptors. Different linguistic consensus models have successfully dealt with these GDM problems. However, recently it has been pointed out that in GDM problems dealing with linguistic information may be necessary to offer a higher flexibility to experts for eliciting their preferences to manage mainly their hesitancy about linguistic assessments when a single linguistic term does not adjust enough to their knowledge/preference. This contribution provides a novel consensus model for GDM problems dealing with Hesitant Fuzzy Linguistic Term Sets (HFLTS) that have been proposed to deal with hesitancy in linguistic GDM problems.","PeriodicalId":312629,"journal":{"name":"2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129630956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12