Hybrid Soft Computing Approaches [electronic resource] : Research and Applications / edited by Siddhartha Bhattacharyya, Paramartha Dutta, Susanta Chakraborty.
Contributor(s): Bhattacharyya, Siddhartha [editor.]
| Dutta, Paramartha [editor.] | Chakraborty, Susanta [editor.] | SpringerLink (Online service).
Material type: 
BookSeries: Studies in Computational Intelligence: 611Publisher: New Delhi : Springer India : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: XIV, 457 p. 154 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9788132225447.Subject(s): Computational intelligence | Artificial intelligence | Software engineering | Computational Intelligence | Artificial Intelligence | Software EngineeringAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
In:
Springer Nature eBookSummary: 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 ParaOptiMUSIG 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.
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 ParaOptiMUSIG 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.
There are no comments for this item.