Hybrid Soft Computing Approaches: Research and Applications by Siddhartha BhattacharyyaHybrid Soft Computing Approaches: Research and Applications by Siddhartha Bhattacharyya

Hybrid Soft Computing Approaches: Research and Applications

bySiddhartha BhattacharyyaEditorParamartha Dutta, Susanta Chakraborty

Hardcover | September 2, 2015

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The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by Para Optimus LG Activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis, (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

Dr. Siddhartha Bhattacharyya did his Bachelors in Physics and Optics and Optoelectronics and Masters in Optics and Optoelectronics from University of Calcutta, India in 1995, 1998 and 2000, respectively. He completed PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is currently an Associate Professor ...
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Title:Hybrid Soft Computing Approaches: Research and ApplicationsFormat:HardcoverDimensions:457 pagesPublished:September 2, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:8132225430

ISBN - 13:9788132225430

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Table of Contents

Section 1. Hybrid Soft Computing Approaches: Research Chapter 1. A Hybrid CS-GSA Algorithm for Optimization.-Chapter 2. Study of Economic Load Dispatch by Various Hybrid Optimization Techniques.-Chapter 3. Unsolved Problems of Ambient Computationally Intelligent TBM Algorithms.-Chapter 4. Hybridizing Differential Evolution Variants through Heterogeneous Mixing in a Distributed Framework.-Section 2. Hybrid Soft Computing Approaches: Applications Chapter 5. Collaborative Simulated Annealing Genetic Algorithm for Geometric Optimization of Thermo-electric Coolers.-Chapter 6. Color Magnetic Resonance Brain Image Segmentation by Para Opti MUSIG Activation Function: An Application.-Chapter 7. Convergence Analysis of Back Propagation Algorithm for Designing an Intelligent System for Sensing Manhole Gases.-Chapter 8. REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition.-Chapter 9. A Soft Computing Approach for Targeted Product Promotion on Social Networks.-Chapter 10. Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis.-Chapter 11. A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms.-Chapter 12. Neuro-Fuzzy Hybridized Model for Seasonal Rainfall Forecasting: A Case Study in Stock Index Forecasting.-Chapter 13. Hybridization of 2D-3D Images for Human Face Recognition.-Chapter 14. Neutrosophic Trust Evaluation Model in B2C E-commerce.-Chapter 15. Immune Based Feature Selection in Rigid Medical Image Registration Using Supervised Neural Network.