Swarm, Evolutionary, and Memetic Computing - Bijaya Ketan Panigrahi

Swarm, Evolutionary, and Memetic Computing

5th International Conference, SEMCCO 2014, Bhubaneswar, India, December 18-20, 2014, Revised Selected Papers

Bijaya Ketan Panigrahi (Redaktør) ; Ponnuthurai Nagaratnam Suganthan (Redaktør) ; Swagatam Das (Redaktør)

This volume constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2014, held in Bhubaneswar, India, in December 2014. Les mer
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Legg i
Vår pris: 1435,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

This volume constitutes the thoroughly refereed post-conference proceedings of the 5th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2014, held in Bhubaneswar, India, in December 2014.

The total of 96 papers presented in this volume was carefully reviewed and selected from 250 submissions for inclusion in the proceedings. The papers cover a wide range of topics in swarm, evolutionary, memetic and other intelligent computing algorithms and their real world applications in problems selected from diverse domains of science and engineering.
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Forlag: Springer International Publishing AG
Innbinding: Paperback
Språk: Engelsk
Sider: 881
ISBN: 9783319202938
Format: 24 x 16 cm
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Differential Evolution with Two Subpopulations.- Intelligent Water Drops Algorithm for Multimodal Spaces.- Glowworm Swarm based Informative attribute.- Simultaneous Feature Selection and Classification.- TLBO Based Hybrid Forecasting Model for Prediction of Exchange Rates.- Evaluating Internet Information Search Channels using Hybrid MCDM technique.- Image Restoration with Fuzzy Coefficient Driven Anisotropic Diffusion.- Principal Component Analysis and General Regression Auto Associative Neural Network Hybrid as One-Class Classifier.- Software Effort Estimation Using Functional Link Neural Networks Tuned with Active Learning and Optimized with Particle Swarm Optimization.- Fraud Detection in Financial Statements using Evolutionary Computation based Rule Miners.- A Fuzzy Entropy based Multi-level Image Thresholding using Differential Evolution.