Artificial Intelligence and Evolutionary Computations in Engineering Systems

This book gathers selected papers presented at the 6th International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, held at the Anna University, Chennai, India, from 20 to 22 April 2020. It covers advances and recent developments in various computational intelligence techniques, with an emphasis on the design of communication systems. In addition, it shares valuable insights into advanced computational methodologies such as neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning methods and their application to decision-making and problem-solving in mobile and wireless communication networks.

Chapter 1. Design and Construction of a Dual Axis Solar Tracking System by Astronomical Algorithm.- Chapter 2. Estimation of Magnetic Flux linkage in SRM using various defuzzification techniques.- Chapter 3. Multilevel Inverter based STATCOM for Distribution System.- Chapter 4. Sensitivity Analysis and Design Optimization of Synchronous Reluctance and Permanent Magnet Motors.- Chapter 5. A New Heuristic algorithm for Economic Load Dispatch incorporating wind power.- Chapter 6. Enhanced Grasshopper Optimization Algorithm For Numerical Optimization.- Chapter 7. Eco-Routing – To Reduce Vehicle CO2 Emissions by CACC: An IoT Application.- Chapter 8. Fuzzy Sliding Mode Control of DC-DC Boost Converter with  Right-Half Plane Zero.- Chapter 9. Liquid Level Control of Non Linear Process Using Big Bang - Big Crunch Optimization Based Controller.- Chapter 10. Impact of PV Cells and MPPT Controller on Power System Dynamics.- Chapter 11. Wavelet Feature Based Microcalcification Detection in Mammogram.- Chapter 12. Reliable Radiation Hardened Memory Cells for Single-Event Multiple Effects.- Chapter 13. Finger Vein Identification Using Deep Convolutional Generative Adversarial Networks.- Chapter 14. Computer Aided Detection of Malignant Mass in Mammogram using U-Net Architecture.- Chapter 15. Visualization and Evaluation of Methane Gas Leakage by Thermal Image Processing using Supervised Deep Learning Models.