2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)最新文献_第3页

Fuzzy fractional variational problems under Jumarie's Riemann-Liouville H-differentiability Jumarie Riemann-Liouville h -可微性下的模糊分数变分问题

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391703

J. Soolaki, O. S. Fard, A. H. Borzabadi

引用次数: 0

Fuzzy n-fold Boolean ideals in BL-algebras bl -代数中的模糊n重布尔理想

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391678

A. Paad

引用次数: 1

Optimal DG placement and capacity allocation using intelligent algorithms 使用智能算法优化DG布局和容量分配

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391657

P. Alinezhad, Omid Zhoulai Bakhoda, M. Menhaj

{"title":"Optimal DG placement and capacity allocation using intelligent algorithms","authors":"P. Alinezhad, Omid Zhoulai Bakhoda, M. Menhaj","doi":"10.1109/CFIS.2015.7391657","DOIUrl":"https://doi.org/10.1109/CFIS.2015.7391657","url":null,"abstract":"Now a Day, using distributed generators (DGs) as power generator resources in Distribution Networks, is growing increasingly. DG installation will cause many advantages such as power loss reduction, increasing reliability, improving voltage profile, power quality and etc. Therefore, proposing an optimal pattern for installing DGs, attracts lots of attention these days. This paper proposes an optimal DGs' placement for Sirou-Feeder in Qom's distribution substation. The problem is considered from the viewpoint of supplier company which itself is both investor and installer of DGs and consequently, both economical and marketing constraints should be considered beside technical constraints. A multi-objective cost function will be defined to reach all objectives, means optimal placement and power allocation of DGs, loss reduction, voltage profile improvement, reliability increase and decreasing DGs' installation costs. Three intelligent algorithms, PSO, GA and GSA, are examined here. The simulation results indicate efficiency of applied methods in solution finding and dominancy of GSA over PSO and GA in optimal placement.","PeriodicalId":239692,"journal":{"name":"2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127600181","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

On the solution of fractional geometric programming problem with fuzzy coefficient 带有模糊系数的分数阶几何规划问题的解

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391697

F. Zahmatkesh, B. Cao

引用次数: 3

A GOP-level fuzzy logic rate controller for high efficiency video coding standard 一种用于高效视频编码标准的gop级模糊逻辑速率控制器

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391680

Davoud Fani, M. Rezaei

引用次数: 1

MPPT for a three-phase grid-connected PV system (Fuzzy Logic Controller vs. PI Controller) 三相并网光伏系统的MPPT(模糊逻辑控制器与PI控制器)

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391666

Omid Zhoulai Bakhoda, M. Menhaj, G. Gharehpetian

引用次数: 5

A fuzzy approach on consensus of nonlinear leader-follower multi-agent systems 非线性领导-随从多智能体系统一致性的模糊方法

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391702

Pegah Tabari Saadi, M. Mardani, M. Shasadeghi, B. Safarinezhadian

引用次数: 0

An independent-layer fuzzy rate controller for streaming applications of H.264/SVC standard 基于H.264/SVC标准的独立层模糊速率控制器

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391687

M. Shojaei, M. Rezaei, A. Samiee

引用次数: 1

Robust deep neural network for wind speed prediction 用于风速预测的鲁棒深度神经网络

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391664

Mahdi Khodayar, M. Teshnehlab

{"title":"Robust deep neural network for wind speed prediction","authors":"Mahdi Khodayar, M. Teshnehlab","doi":"10.1109/CFIS.2015.7391664","DOIUrl":"https://doi.org/10.1109/CFIS.2015.7391664","url":null,"abstract":"Wind speed prediction is a basic requirement of wind energy generation with large generation capacity for large-scale wind power penetration. The intermittency and stochastic quality of wind speed leads to a big challenge for high penetration of wind power in electricity systems due to error-prone wind speed prediction methods. There are many artificial neural network (ANN) approaches proposed in the recent literature in order to tackle this problem. However, hand engineering features and applying shallow architectures can lead to poor prediction performance in these methodologies. Deep neural networks are ANNs with great generalization capability that can automatically extract meaningful features from the data with as less prior knowledge as possible. In this paper we propose a stacked auto-encoder (SAE) neural network for ultra-short-term and short-term wind speed prediction. To the best of our knowledge this is the first paper that applies deep learning on wind speed prediction of a wind site. Moreover, a rough regression layer is applied at the top of this model in order to deal with uncertainty factors existing in the wind speed data. Experimental results show significant improvement compared to other ANN methods that applied shallow architectures in the literature and the traditional SAE.","PeriodicalId":239692,"journal":{"name":"2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)","volume":"131 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125792549","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: 30

The prediction of increase or decrease of electricity cost using fuzzy expert systems 利用模糊专家系统对电力成本增减进行预测

2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) Pub Date : 2015-09-01 DOI: 10.1109/CFIS.2015.7391641

Mina Asadi Sanjani

{"title":"The prediction of increase or decrease of electricity cost using fuzzy expert systems","authors":"Mina Asadi Sanjani","doi":"10.1109/CFIS.2015.7391641","DOIUrl":"https://doi.org/10.1109/CFIS.2015.7391641","url":null,"abstract":"Expert systems are computer programs which are designed to perform the job of an expert, and also to dramatize their behavior. An expert system is important with the aim of implementing computer systems rather than human beings in decision making. The energy of strategic goods is considered in international levels. Activities of the government and organizations depend on the product and its related markets. In fact, the prediction of electric load is considered as the first square in decision making, and planning power systems. Since performing these decisions is time consuming and requires huge financial budgets, prediction of electric load can be considered as a necessary and vital issue in power systems. According to the examination of country's electric importing and exporting and the load peak of annual electric usage, the purpose is to predict the occurred electric load and with the application of statistical information related to the used load peak, the import and export of electric power in the recent years, this system will have the capacity to check the electric cost and will predict the increase or decrease of it. The performance of the fuzzy expert system was evaluated using an receiver operating characteristic curve, which provides the accuracy of 87%. In order to test the correctness of system function, the analysis of receiver operating characteristic curves are used.","PeriodicalId":239692,"journal":{"name":"2015 4th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122394709","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