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    Using genetic alghoritm for distributed generation allocation to reduce losses and improve voltage profile

    , Article 42nd International Universities Power Engineering Conference, UPEC 2007, Brighton, 4 September 2007 through 6 September 2007 ; 2007 , Pages 954-959 ; 1905593368 (ISBN); 9781905593361 (ISBN) Alinejad Beromi, Y ; Sedighizadeh, M ; Bayat, M. R ; Khodayar, M. E ; Sharif University of Technology
    This paper presents a method for the optimal allocation of Distributed generation in distribution systems. In this paper, our aim would be optimal distributed generation allocation for voltage profile improvement and loss reduction in distribution network. Genetic Algorithm (GA) was used as the solving tool, which referring two determined aim; the problem is defined and objective function is introduced. Considering to fitness values sensitivity in genetic algorithm process, there is needed to apply load flow for decision-making. Load flow algorithm is combined appropriately with GA, till access to acceptable results of this operation. We used MATPOWER package for load flow algorithm and... 

    Constructing interpretable genetic fuzzy rule-based system for breast cancer diagnostic

    , Article Proceedings of the 2009 WRI Global Congress on Intelligent Systems, GCIS 2009, 19 May 2009 through 21 May 2009, Xiamen ; Volume 1 , 2009 , Pages 441-446 ; 9780769535715 (ISBN) Sedighiani, K ; HashemiKhabir, S ; Sharif University of Technology
    This paper shows how a subset of features can be selected for designing interpretable fuzzy rule-based system. This method consists of two phases: feature subset selection based on Michigan Learning approach and Training fuzzy rule-based system using the selected subset from the first phase. First, a number of independent fuzzy rule-based systems are trained using genetic operations, and then the dominated rules of each trained system with the highest fitness values are selected. From the selected rules, a pre-specified number of features are chosen with the highest frequency. In the second phase, a fuzzy rule-based system is trained based on the selected features from the previous phase.... 

    Is independent component analysis appropriate for multivariate resolution in analytical chemistry?

    , Article TrAC - Trends in Analytical Chemistry ; Volume 31 , 2012 , Pages 134-143 ; 01659936 (ISSN) Parastar, H ; Jalali Heravi, M ; Tauler, R ; Sharif University of Technology
    In this article, we examine Independent Component Analysis (ICA) and the concept of Mutual information (MI) as a quantitative measure of independence from the point of view of analytical chemistry. We compare results obtained by different ICA methods with results obtained by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). These results have shown that, when non-negativity constraints are applied, values of MI increase considerably and the resolved components cannot anymore be considered to be independent (i.e. they can only be considered to be the " least dependent" components). MI values of profiles resolved by MCR-ALS and ICA did not differ significantly when...