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Table of Contents
Оглавление1 Cover
4 Preface
5 1 Introduction to Nature-Inspired Computing 1.1 Introduction 1.2 Aspiration From Nature 1.3 Working of Nature 1.4 Nature-Inspired Computing 1.5 General Stochastic Process of Nature-Inspired Computation References
6 2 Applications of Hybridized Algorithms and Novel Algorithms in the Field of Machine Learning 2.1 Introduction of Genetic Algorithm 2.2 Introduction to Artificial Bear Optimization (ABO) 2.3 Performance Evaluation 2.4 What is Next? References
7 3 Efficiency of Finding Best Solutions Through Ant Colony Optimization (ACO) Technique 3.1 Introduction 3.2 A Case Study on Surgical Treatment in Operation Room 3.3 Case Study on Waste Management System 3.4 Working Process of the System 3.5 Background Knowledge to be Considered for Estimation 3.6 Case Study on Traveling System 3.7 Future Trends and Conclusion References
8 4 A Hybrid Bat-Genetic Algorithm–Based Novel Optimal Wavelet Filter for Compression of Image Data 4.1 Introduction 4.2 Review of Related Works 4.3 Existing Technique for Secure Image Transmission 4.4 Proposed Design of Optimal Wavelet Coefficients for Image Compression 4.5 Results and Discussion 4.6 Conclusion References
9 5 A Swarm Robot for Harvesting a Paddy Field 5.1 Introduction 5.2 Second Case Study on Recommendation Systems 5.3 Third Case Study on Weight Lifting Robot 5.4 Background Knowledge of Harvesting Process 5.5 Future Trend and Conclusion References
10 6 Firefly Algorithm 6.1 Introduction 6.2 Firefly Algorithm 6.3 Applications of Firefly Algorithm 6.4 Why Firefly Algorithm is Efficient 6.5 Discussion and Conclusion References
11 7 The Comprehensive Review for Biobased FPA Algorithm 7.1 Introduction 7.2 Related Work to FPA 7.3 Limitations 7.4 Future Research 7.5 Conclusion References
12 8 Nature-Inspired Computation in Data Mining 8.1 Introduction 8.2 Classification of NIC 8.3 Evolutionary Computation 8.4 Biological Neural Network 8.5 Molecular Biology 8.6 Immune System 8.7 Applications of NIC in Data Mining 8.8 Conclusion References
13 9 Optimization Techniques for Removing Noise in Digital Medical Images 9.1 Introduction 9.2 Medical Imaging Techniques 9.3 Image Denoising 9.4 Optimization in Image Denoising 9.5 Results and Discussions 9.6 Conclusion and Future Scope References
14 10 Performance Analysis of Nature-Inspired Algorithms in Breast Cancer Diagnosis 10.1 Introduction 10.2 Related Works 10.3 Dataset: Wisconsin Breast Cancer Dataset (WBCD) 10.4 Ten-Fold Cross-Validation 10.5 Naive Bayesian Classifier 10.6 K-Means Clustering 10.7 Support Vector Machine (SVM) 10.8 Swarm Intelligence Algorithms 10.9 Evaluation Metrics 10.10 Results and Discussion 10.11 Conclusion References
15 11 Applications of Cuckoo Search Algorithm for Optimization Problems 11.1 Introduction 11.2 Related Works 11.3 Cuckoo Search Algorithm 11.4 Applications of Cuckoo Search 11.5 Conclusion and Future Work References
16 12 Mapping of Real-World Problems to Nature-Inspired Algorithm Using Goal-Based Classification and TRIZ 12.1 Introduction and Background 12.2 Motivations Behind NIA Exploration 12.3 Novel TRIZ + NIA Approach 12.4 Examples to Support the TRIZ + NIA Approach 12.5 A Solution of NP-H Using NIA 12.6 Conclusion References
17 Index
