Coverart for item
The Resource Applied nature-inspired computing : algorithms and case studies, Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors

Applied nature-inspired computing : algorithms and case studies, Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors

Label
Applied nature-inspired computing : algorithms and case studies
Title
Applied nature-inspired computing
Title remainder
algorithms and case studies
Statement of responsibility
Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors
Contributor
Subject
Language
eng
Summary
This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each. Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management
Member of
Cataloging source
EBLCP
Dewey number
006.3/82
Index
no index present
LC call number
QA76.9.N37
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
  • 1984-
  • 1975-
  • 1975-
http://library.link/vocab/relatedWorkOrContributorName
  • Dey, Nilanjan
  • Ashour, Amira
  • Bhattacharyya, Siddhartha
Series statement
Springer Tracts in Nature-Inspired Computing Ser
http://library.link/vocab/subjectName
Natural computation
Label
Applied nature-inspired computing : algorithms and case studies, Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors
Instantiates
Publication
Note
5 Conclusion
Antecedent source
file reproduced from an electronic resource
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Contents; About the Editors; Particle Swarm Optimization of Morphological Filters for Electrocardiogram Baseline Drift Estimation; 1 Introduction; 2 Morphological Filters; 2.1 Morphological Dilation and Erosion; 2.2 Morphological Opening and Closing; 3 Morphological ECG Baseline Estimation; 3.1 One-Stage Morphological ECG Baseline Estimation; 3.2 Two-Stage Morphological ECG Baseline Estimation; 4 Particle Swarm Optimization; 4.1 Strategy of PSO; 4.2 General Communication Strategy by Taking Two Human Particles; 4.3 Structure of Artificial Particle
  • 5 Particle Swarm Optimized (PSO) Morphological ECG Baseline Estimation5.1 The Objective of the Optimization; 5.2 Two-Stage PSO Optimization; 6 Results and Discussion; 7 Conclusion; References; Detection of Breast Cancer Using Fusion of MLO and CC View Features Through a Hybrid Technique Based on Binary Firefly Algorithm and Optimum-Path Forest Classifier; 1 Introduction; 2 Related Studies; 3 Materials and Methods; 3.1 Preprocessing and Segmentation; 3.2 Feature Extraction; 3.3 Feature Fusion; 3.4 Optimum-Path Forest Classifier; 3.5 Binary Firefly Algorithm Based Feature Selection
  • 3.6 Classification4 Results and Discussions; 5 Conclusion; References; Recommending Healthy Personalized Daily Menus-A Cuckoo Search-Based Hyper-Heuristic Approach; 1 Introduction; 2 Related Work; 3 Problem Formulation; 3.1 Solution of the Optimization Problem; 3.2 Fitness Function; 4 Cuckoo Search Based Hyper-Heuristic; 4.1 Overview of Cuckoo Search; 4.2 Cuckoo Search Based Hyper-Heuristic Algorithm; 5 Performance Evaluation; 5.1 System Architecture; 5.2 Experimental Setup; 5.3 Experimental Results; 5.4 Comparative Evaluation; 6 Conclusions and Future Work; References
  • A Hybrid Bat-Inspired Algorithm for Power Transmission Expansion Planning on a Practical Brazilian Network1 Introduction; 1.1 Contributions; 1.2 Organization; 2 Background and Related Works; 2.1 Bat Algorithm Approaches; 2.2 Additional Methods for Optimizing the Metaheuristics' Algorithm; 2.3 Southern System; 3 Problem Formulation; 3.1 TEP Formulation; 3.2 The Decomposition Problem; 3.3 The Proposed Search-Space Shrinking (SSS); 3.4 The Proposed Adapted Bat Algorithm (ABA); 4 Results and Discussion; 5 Discussion and Conclusions; 5.1 Why Adapted Bat-Inspired Algorithm Is Efficient
  • 5.2 Further Research TopicsReferences; An Application of Binary Grey Wolf Optimizer (BGWO) Variants for Unit Commitment Problem; 1 Introduction; 1.1 Motivation; 1.2 Related Work; 2 Problem Formulation; 2.1 Objective Function; 2.2 System Constraints; 2.3 Thermal Unit Constraints; 3 Solution Methodology; 3.1 Overview of GWO; 3.2 Proposed BGWO Approaches; 3.3 BGWO Implementation to Solve UCP; 3.4 Constraint Repair; 4 Results and Discussion; 4.1 Numerical Results and Discussion:Test System 1; 4.2 Numerical Results and Discussion: Test System 2; 4.3 Numerical Results and Discussion: Test System 3
Dimensions
unknown
Extent
1 online resource (281 pages)
File format
one file format
Form of item
online
Isbn
9789811392634
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-981-13-9
Quality assurance targets
unknown
Reformatting quality
unknown
Specific material designation
remote
System control number
  • on1112420923
  • (OCoLC)1112420923
Label
Applied nature-inspired computing : algorithms and case studies, Nilanjan Dey, Amira S. Ashour, Siddhartha Bhattacharyya, editors
Publication
Note
5 Conclusion
Antecedent source
file reproduced from an electronic resource
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Contents; About the Editors; Particle Swarm Optimization of Morphological Filters for Electrocardiogram Baseline Drift Estimation; 1 Introduction; 2 Morphological Filters; 2.1 Morphological Dilation and Erosion; 2.2 Morphological Opening and Closing; 3 Morphological ECG Baseline Estimation; 3.1 One-Stage Morphological ECG Baseline Estimation; 3.2 Two-Stage Morphological ECG Baseline Estimation; 4 Particle Swarm Optimization; 4.1 Strategy of PSO; 4.2 General Communication Strategy by Taking Two Human Particles; 4.3 Structure of Artificial Particle
  • 5 Particle Swarm Optimized (PSO) Morphological ECG Baseline Estimation5.1 The Objective of the Optimization; 5.2 Two-Stage PSO Optimization; 6 Results and Discussion; 7 Conclusion; References; Detection of Breast Cancer Using Fusion of MLO and CC View Features Through a Hybrid Technique Based on Binary Firefly Algorithm and Optimum-Path Forest Classifier; 1 Introduction; 2 Related Studies; 3 Materials and Methods; 3.1 Preprocessing and Segmentation; 3.2 Feature Extraction; 3.3 Feature Fusion; 3.4 Optimum-Path Forest Classifier; 3.5 Binary Firefly Algorithm Based Feature Selection
  • 3.6 Classification4 Results and Discussions; 5 Conclusion; References; Recommending Healthy Personalized Daily Menus-A Cuckoo Search-Based Hyper-Heuristic Approach; 1 Introduction; 2 Related Work; 3 Problem Formulation; 3.1 Solution of the Optimization Problem; 3.2 Fitness Function; 4 Cuckoo Search Based Hyper-Heuristic; 4.1 Overview of Cuckoo Search; 4.2 Cuckoo Search Based Hyper-Heuristic Algorithm; 5 Performance Evaluation; 5.1 System Architecture; 5.2 Experimental Setup; 5.3 Experimental Results; 5.4 Comparative Evaluation; 6 Conclusions and Future Work; References
  • A Hybrid Bat-Inspired Algorithm for Power Transmission Expansion Planning on a Practical Brazilian Network1 Introduction; 1.1 Contributions; 1.2 Organization; 2 Background and Related Works; 2.1 Bat Algorithm Approaches; 2.2 Additional Methods for Optimizing the Metaheuristics' Algorithm; 2.3 Southern System; 3 Problem Formulation; 3.1 TEP Formulation; 3.2 The Decomposition Problem; 3.3 The Proposed Search-Space Shrinking (SSS); 3.4 The Proposed Adapted Bat Algorithm (ABA); 4 Results and Discussion; 5 Discussion and Conclusions; 5.1 Why Adapted Bat-Inspired Algorithm Is Efficient
  • 5.2 Further Research TopicsReferences; An Application of Binary Grey Wolf Optimizer (BGWO) Variants for Unit Commitment Problem; 1 Introduction; 1.1 Motivation; 1.2 Related Work; 2 Problem Formulation; 2.1 Objective Function; 2.2 System Constraints; 2.3 Thermal Unit Constraints; 3 Solution Methodology; 3.1 Overview of GWO; 3.2 Proposed BGWO Approaches; 3.3 BGWO Implementation to Solve UCP; 3.4 Constraint Repair; 4 Results and Discussion; 4.1 Numerical Results and Discussion:Test System 1; 4.2 Numerical Results and Discussion: Test System 2; 4.3 Numerical Results and Discussion: Test System 3
Dimensions
unknown
Extent
1 online resource (281 pages)
File format
one file format
Form of item
online
Isbn
9789811392634
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other control number
10.1007/978-981-13-9
Quality assurance targets
unknown
Reformatting quality
unknown
Specific material designation
remote
System control number
  • on1112420923
  • (OCoLC)1112420923

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