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Hybrid Soft Computing Approaches

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Cover of 'Hybrid Soft Computing Approaches'

Table of Contents

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    Book Overview
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    Chapter 1 A Hybrid CS–GSA Algorithm for Optimization
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    Chapter 2 Study of Economic Load Dispatch by Various Hybrid Optimization Techniques
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    Chapter 3 Unsolved Problems of Ambient Computationally Intelligent TBM Algorithms
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    Chapter 4 Hybridizing Differential Evolution Variants Through Heterogeneous Mixing in a Distributed Framework
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    Chapter 5 Collaborative Simulated Annealing Genetic Algorithm for Geometric Optimization of Thermo-electric Coolers
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    Chapter 6 Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG Activation Function: An Application
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    Chapter 7 Convergence Analysis of Backpropagation Algorithm for Designing an Intelligent System for Sensing Manhole Gases
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    Chapter 8 REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition
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    Chapter 9 A Soft Computing Approach for Targeted Product Promotion on Social Networks
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    Chapter 10 Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis
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    Chapter 11 A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection Using Breast Thermograms
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    Chapter 12 Neuro-Fuzzy Hybridized Model for Seasonal Rainfall Forecasting: A Case Study in Stock Index Forecasting
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    Chapter 13 Hybridization of 2D-3D Images for Human Face Recognition
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    Chapter 14 Neutrosophic Trust Evaluation Model in B2C E-Commerce
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    Chapter 15 Immune-Based Feature Selection in Rigid Medical Image Registration Using Supervised Neural Network
Attention for Chapter 8: REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition
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Chapter title
REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition
Chapter number 8
Book title
Hybrid Soft Computing Approaches
Published by
Springer India, August 2015
DOI 10.1007/978-81-322-2544-7_8
Book ISBNs
978-8-13-222543-0, 978-8-13-222544-7
Authors

Goran Klepac, Robert Kopal, Leo Mršić

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Other 2 25%
Professor 1 13%
Unspecified 1 13%
Student > Master 1 13%
Other 0 0%
Unknown 1 13%
Readers by discipline Count As %
Engineering 3 38%
Business, Management and Accounting 1 13%
Unspecified 1 13%
Decision Sciences 1 13%
Computer Science 1 13%
Other 0 0%
Unknown 1 13%