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    Inferring signaling pathways using interventional data

    , Article Intelligent Data Analysis ; Volume 17, Issue 2 , April , 2013 , Pages 295-308 ; 1088467X (ISSN) Mazloomian, A ; Beigy, H ; Sharif University of Technology
    2013
    Abstract
    Studying biological networks helps to gain a better understanding of cellular behaviors. One of the prominent models to study complex interactions in biological networks is the Nested Effects Model (NEM). Based on the Nested Effects Model, we propose two methods for inferring signaling pathways from interventional data. In the first method, we search the space of all feasible solutions with an evolutionary approach to maximize a standard Bayesian score. In the second method, sub-models are constructed with informative features and then combined using an averaging method to make the analysis of larger networks computationally possible. We tested our proposed methods in various noise levels on... 

    Symbiotic evolutionary algorithm, a remedy for linkage problem

    , Article International Journal of Computational Intelligence and Applications ; Volume 8, Issue 3 , 2009 , Pages 237-252 ; 14690268 (ISSN) Halavati, R ; Bagheri Shouraki, S ; Sharif University of Technology
    2009
    Abstract
    Recombination in Genetic Algorithms (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations, hopefully producing an offspring that has the good characteristics of both parents, and this requires explicit chromosome and recombination, operator by design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination, and by using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets: combinatorial optimization category, deceptive problems, and fully deceptive... 

    Evolutionary coincidence-based ontology mapping extraction

    , Article Expert Systems ; Volume 25, Issue 3 , 2008 , Pages 221-236 ; 02664720 (ISSN) Qazvinian, V ; Abolhassani, H ; Haeri, S. H ; Bagheri Hariri, B ; Sharif University of Technology
    2008
    Abstract
    Ontology matching is a process for selection of a good alignment across entities of two (or more) ontologies. This can be viewed as a two-phase process of (1) applying a similarity measure to find the correspondence of each pair of entities from two ontologies, and (2) extraction of an optimal or near optimal mapping. This paper is focused on the second phase and introduces our evolutionary approach for that. To be able to do so, we need a mechanism to score different possible mappings. Our solution is a weighting mechanism named coincidence-based weighting. A genetic algorithm is then introduced to create better mappings in successive iterations. We will explain how we code a mapping as... 

    An approach for under voltage load shedding using particle swarm optimization

    , Article International Symposium on Industrial Electronics 2006, ISIE 2006, Montreal, QC, 9 July 2006 through 13 July 2006 ; Volume 3 , 2006 , Pages 2019-2024 ; 1424404975 (ISBN); 9781424404971 (ISBN) Mozafari, B ; Amraee, T ; Ranjbar, A. M ; Sharif University of Technology
    2006
    Abstract
    Under voltage load shedding (UVLS) is one of the most powerful countermeasure and somehow an economical solution to sustain voltage stability especially for double or severe contingencies in power systems. In this paper the concept of dynamic security-constrained OPF is employed to develop a model for optimal UVLS. Considering dynamic voltage security, the presented model attempts to provide sufficient voltage stability margin for post contingency condition. This is done by means of interruption some portion of loads at minimum cost. The voltage stability margin, which is measured as a MW distance to the collapse point, is incorporated into the power flow equations. Although some powerful...