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Intro
Preface
List of Reviewers
Contents
Editors and Contributors
Smart Design and Its Applications: Challenges and Techniques
1 Introduction
2 Some Applications for Smart Design
2.1 City and Environment
2.2 Intelligent Networking
2.3 Security and Management
3 Some Techniques for Smart Design
4 Conclusions
References
City and Environment
Automatic Generation Control Scheme for Power Quality Improvement of Multi-source Power Generating System with Secondary Controller Optimization Using Parameter-Setting-Free Harmony Search
1 Introduction

2 Single-Area Multi-source Power System Modeling
3 Controller Design
4 Proposed Parameter-Setting-Free Harmony Search Algorithm-Tuned PID Controller
5 Simulation Results and Discussions
6 Conclusion
References
Environmental Sound Classification Using Neural Network and Deep Learning
1 Introduction
1.1 Scope
2 Related Work
3 Problem Formulation
3.1 Segmenting an Audio Signal Into Windows
4 Feature Extraction
4.1 Features Used for Training the Neural Network
5 Designing the Cost Function for Bayesian Regularised Neural Network

5.1 Over-Fitting and Regularization of Neural Networks
5.2 Bayesian Regularization
6 Bayesian Regularised Neural Networks for Urban Sound Noise Classification: A Deep Learning Approach
6.1 Deep Neural Network Design
6.2 Novel Design: Two Input-Output Neural Network Model
6.3 Classification of Multiple Sound Source
6.4 Novel Approach: Multi-label Classification Using Bayesian Regularized Fitnet Model and Deep Lerning Approach
7 Conclusion and Future Work
8 Problems
8.1 Feature Extraction
8.2 Designing of Optimal Neural Network
8.3 Single Label Detection

8.4 Multi Label Detection
References
Feature Selection Method Using CFO and Rough Sets for Medical Dataset
1 Introduction
2 Preliminaries
2.1 Central Force Optimization
2.2 Rough Set Theory
3 Proposed Algorithm
3.1 Preprocessing of Gene Expression Data
3.2 Fitness Function
4 Experimental Result
4.1 Parameter Setting and Datasets
4.2 Results and Discussion
5 Conclusion
References
Fuzzy-Based Optimal Solution for Minimization of Loss of Company Based on Uncertain Environment
1 Introduction
2 Related Works
3 Proposed Method

4 Simulation and Analysis
5 Conclusions
References
Intelligent Networking
Impacts of Computational Techniques for Wireless Sensor Networks
1 Introduction
1.1 WSN: Basic Introduction
1.2 WSN: Basic Application Area
2 Need of Optimization
3 Description of Applied Algorithm
3.1 Dragonfly Algorithm
3.2 Quasi-opposition Atom Search Optimization (QOASO) Algorithm
3.3 Pathfinder Algorithm (PA)
3.4 Salp Swarm Algorithm
4 Optimization Techniques Applied in WSN
4.1 Modeling of Consumption of Energy
4.2 Path Loss Model
4.3 System Lifetime Model

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