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Nature-Inspired Optimizers

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Cover of 'Nature-Inspired Optimizers'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Nature-Inspired Algorithms
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    Chapter 2 Ant Colony Optimizer: Theory, Literature Review, and Application in AUV Path Planning
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    Chapter 3 Ant Lion Optimizer: Theory, Literature Review, and Application in Multi-layer Perceptron Neural Networks
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    Chapter 4 Dragonfly Algorithm: Theory, Literature Review, and Application in Feature Selection
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    Chapter 5 Genetic Algorithm: Theory, Literature Review, and Application in Image Reconstruction
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    Chapter 6 Grey Wolf Optimizer: Theory, Literature Review, and Application in Computational Fluid Dynamics Problems
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    Chapter 7 Grasshopper Optimization Algorithm: Theory, Literature Review, and Application in Hand Posture Estimation
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    Chapter 8 Multi-verse Optimizer: Theory, Literature Review, and Application in Data Clustering
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    Chapter 9 Moth-Flame Optimization Algorithm: Theory, Literature Review, and Application in Optimal Nonlinear Feedback Control Design
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    Chapter 10 Particle Swarm Optimization: Theory, Literature Review, and Application in Airfoil Design
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    Chapter 11 Salp Swarm Algorithm: Theory, Literature Review, and Application in Extreme Learning Machines
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    Chapter 12 Sine Cosine Algorithm: Theory, Literature Review, and Application in Designing Bend Photonic Crystal Waveguides
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    Chapter 13 Whale Optimization Algorithm: Theory, Literature Review, and Application in Designing Photonic Crystal Filters
Attention for Chapter 11: Salp Swarm Algorithm: Theory, Literature Review, and Application in Extreme Learning Machines
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