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Titlebook: Genetic and Evolutionary Computing; Proceedings of the S Jeng-Shyang Pan,Pavel Kr?mer,Václav Sná?el Conference proceedings 2014 Springer In

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書(shū)目名稱Genetic and Evolutionary Computing
副標(biāo)題Proceedings of the S
編輯Jeng-Shyang Pan,Pavel Kr?mer,Václav Sná?el
視頻videohttp://file.papertrans.cn/383/382659/382659.mp4
概述Presents recent research in Genetic and Evolutionary Computing.Proceedings of the is the 7th International Conference on Genetic and Evolutionary Computing ICGEC 2013 held in Prague, Czech Republic, A
叢書(shū)名稱Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Genetic and Evolutionary Computing; Proceedings of the S Jeng-Shyang Pan,Pavel Kr?mer,Václav Sná?el Conference proceedings 2014 Springer In
描述.Genetic and Evolutionary Computing.This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at ICGEC 2013, the 7th International Conference on Genetic and Evolutionary Computing. The conference this year was technically co-sponsored by The Waseda University in Japan, Kaohsiung University of Applied Science in Taiwan, and VSB-Technical University of Ostrava. ICGEC 2013 was held in Prague, Czech Republic. Prague is one of the most beautiful cities in the world whose magical atmosphere has been shaped over ten centuries. Places of the greatest tourist interest are on the Royal Route running from the Powder Tower through Celetna Street to Old Town Square, then across Charles Bridge through the Lesser Town up to the Hradcany Castle. One should not miss the Jewish Town, and the National Gallery with its fine collection of Czech Gothic art, collection of old European art, and a beautiful collection of French art. .The conference was intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. The main topics of ICGEC 2013 included Intelligent Computing, Evolutionary Computing, Genetic C
出版日期Conference proceedings 2014
關(guān)鍵詞Computational Intelligence; Evolutionary Computing; Genetic Computing; Intelligent Systems
版次1
doihttps://doi.org/10.1007/978-3-319-01796-9
isbn_softcover978-3-319-01795-2
isbn_ebook978-3-319-01796-9Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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PSO-2S Optimization Algorithm for Brain MRI Segmentation,, . fitting a sum of Gaussian probability density functions to the image histogram. This problem can be expressed as a continuous nonlinear optimization problem. The goal of this paper is to show the relevance of using a recently proposed variant of the Particle Swarm Optimization (PSO) algorithm, c
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A Swarm Random Walk Algorithm for Global Continuous Optimization,lve these problems approximately, when solving them exactly is impractical. In this class of methods, swarm intelligence (SI) presents metaheuristics that exploit a population of interacting agents able to self–organize, such as ant colony optimization (ACO), particle swarm optimization (PSO), and a
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Object Detection Using Scale Invariant Feature Transform,res from images and it is a useful tool for matching between different views of an object. This paper proposes how the SIFT can be used for an object detection problem, especially human detection problem. The Support Vector Machine (SVM) is adopted as the classifier in the proposed scheme. Experimen
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Nearest Feature Line and Extended Nearest Feature Line with Half Face, are proposed for face recognition. Nearest feature line (NFL) classifier and extended nearest feature line (ENFL) classifier both constitute the feature line by a pair of the samples belonging to the same class. Being different from them, NFLhalfface and ENFLhalfface constitute the feature line by
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Studying Common Developmental Genomes in Hybrid and Symbiotic Formations, previous work, we studied the common properties of several computational architectures consisting of connected computational elements. Their common property of sparsely connected networks, envisages how universal properties and processes can be included in a developmental mapping through an . appro
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Routing and Wavelength Assignment in Optical Networks from Maximum Edge-Disjoint Paths, We propose an algorithm which is based on the maximum number of edge-disjoint paths (MEDP) to solve the RWA problem. The performance of the proposed method has been verified by experiments on several realistic network topologies.
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