2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)最新文献_第3页

Similarity-based method for reduction of fuzzy rules 基于相似度的模糊规则约简方法

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851603

Arturo Garcia-Garcia, M. Reformat, Andres Mendez-Vazquez

引用次数: 2

Performance evaluation of evolving classifier algorithms in high dimensional spaces 高维空间中进化分类器算法的性能评价

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851595

R. Rocha, F. Gomide

引用次数: 2

Crisp to fuzzy ontology conversion in the context of social networks: A new approach 社交网络环境下的模糊本体转换:一种新方法

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851633

Hoda Safaeipour, M. F. Zarandi, S. Bastani

引用次数: 4

Fuzzy weighted average approach to ranking projects in contractor initial bidding 承包商初始招标项目排序的模糊加权平均法

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851608

H. Alhumaidi

引用次数: 2

What if we use different “and”-operations in the same expert system 如果我们在同一个专家系统中使用不同的 "和 "操作，该怎么办？

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851618

Mahdokht Afravi, V. Kreinovich

{"title":"What if we use different “and”-operations in the same expert system","authors":"Mahdokht Afravi, V. Kreinovich","doi":"10.1109/NAFIPS.2016.7851618","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851618","url":null,"abstract":"In expert systems, we often face a problem of estimating the expert's degree of confidence in a composite statement A&B based on the known expert's degrees of confidence a = d(A) and b = d(B) in individual statements A and B. The corresponding estimate f&(a, b) is sometimes called an “and”-operation. Traditional fuzzy logic assumes that the same “and”-operation is applied to all pairs of statements. In this case, it is reasonable to justify that the “and”-operation be associative; such “and”-operations are known as t-norms. In practice, however, in different areas, different “and”-operations provide a good description of expert reasoning. As a result, when we combine expert knowledge from different areas into a single expert system, it is reasonable to use different “and”-operations to combine different statements. In this case, associativity is no longer a natural requirement. We show, however, that in such situations, under some reasonable conditions, associativity of each “and”-operation can still be deduced. Thus, in this case, we can still use associative t-norms.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132656152","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

Computational model for measuring project complexity in construction 施工中项目复杂性度量的计算模型

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851609

L. D. Nguyen, Dai Q. Tran, An T. Nguyen, Long Le-Hoai

引用次数: 5

FuzzRESS: A fuzzy rule-based expert system shell combining positive and negative knowledge for consultation of Vietnamese traditional medicine FuzzRESS:一种基于模糊规则的越南传统医学正负知识相结合的专家系统外壳

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851624

H. Nguyen

引用次数: 6

Generating ternary stock trading signals using fuzzy genetic network programming 利用模糊遗传网络规划生成三元股票交易信号

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851630

Hosein Hamisheh Bahar, M. Zarandi, A. Esfahanipour

{"title":"Generating ternary stock trading signals using fuzzy genetic network programming","authors":"Hosein Hamisheh Bahar, M. Zarandi, A. Esfahanipour","doi":"10.1109/NAFIPS.2016.7851630","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851630","url":null,"abstract":"In this paper, an expert system is developed using fuzzy genetic network programming with reinforcement learning (GNP-RL) in order to generate stock trading signals based on technical indices of the stock prices. In order to increase the accuracy and reliability of results, we applied Wavelet Transform to eliminate noises and irregularities in prices. Since choosing the most appropriate wavelet base is an important decision, the Energy to Shannon Entropy Ratio, as an objective method, is used in order to address this concern. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. The proposed model has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in testing time period shows that the developed system has more favorable performance in comparison with the simple GNP-RL with binary signals and Buy and Hold strategy.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117137250","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: 6

A combined fuzzy aggregation and consensus process for Multi-Criteria Group Decision Making problems 多准则群决策问题的模糊聚合与一致过程

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851611

N. Siraj, M. Omar, A. Fayek

{"title":"A combined fuzzy aggregation and consensus process for Multi-Criteria Group Decision Making problems","authors":"N. Siraj, M. Omar, A. Fayek","doi":"10.1109/NAFIPS.2016.7851611","DOIUrl":"https://doi.org/10.1109/NAFIPS.2016.7851611","url":null,"abstract":"In Multi-Criteria Group Decision Making (MCGDM) problems, aggregation and consensus methods are two key elements in reaching an overall collective value representing the group of experts making the decision. In many instances, the assessment process is based on linguistic terms rather than numerical values. Therefore, fuzzy aggregation and fuzzy consensus methods are more suitable for dealing with the linguistic terms used to reach the final decision. First, we present fuzzy set theory, fuzzy aggregation, and fuzzy consensus. Then, we describe a process for integrating fuzzy aggregation and fuzzy consensus in group decision-making problems. This process considers the aggregation of multiple criteria used for evaluation as well as the degree of consensus between the experts. Finally, we present a hypothetical case study to implement the developed process in MCGDM related to contractor selection. This paper contributes to the body of knowledge by developing a process that applies fuzzy aggregation and fuzzy consensus in solving MCGDM problems in construction. Furthermore, through the application of fuzzy set theory in aggregation and consensus, the developed process assists decision makers in problems that encompass subjectivity and uncertainty in their assessment.","PeriodicalId":208265,"journal":{"name":"2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124960149","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: 3

Modeling of an air conditioning system through techniques of soft-computing 利用软计算技术对空调系统进行建模

2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) Pub Date : 2016-10-01 DOI: 10.1109/NAFIPS.2016.7851596

H. R. D. N. Costa, A. L. Neve

引用次数: 0