Evolutionary Multi-Objective System Design: Theory and Applications

ISBN-13: 9780367572808 / Angielski / Miękka / 2020 / 218 str.

Nadia Nedjah; Luiza De Macedo Mourelle; Heitor Silverio Lopes

Opis

Evolutionary multi-objective optimization (EMO) has emerged as a sub-discipline of multi-objective optimization, combining the fields of evolutionary computation and classical multiple criteria decision making. This field has applications in artificial intelligence, machine learning, and data mining. This book will present new trends, methods, a

Spis treści

Embrittlement of Stainless Steel Coated Electrodes. Learning Fuzzy Rules from Imbalanced Datasets using Multi-objective Evolutionary Algorithms. Hybrid Multi-Objective Evolutionary Algorithms with Collective Intelligence. Multiobjective Particle Swarm Optimization Fuzzy Gain Scheduling Control. Multiobjective evolutionary algorithms for smart placement. Solving Multi-Objective Problems with MOEA/D and Quasi-Simplex Local Search. Multi-objective Evolutionary Design of Robust Substitution Boxes. Multi-objective approach to the Protein Structure Prediction Problem. Multi-objective IP Assignment for Efficient NoC-based System Design.

O autorze

Nadia Nedjah, Luiza De Macedo Mourelle, Heitor Silverio Lopes