Intelligent System Design Based on Soft Computing Models
Description
This book comprises a collection of papers focused on intelligent systems based on soft computing techniques. In this book, new directions on intelligent system design based on soft computing models, such as fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are offered. In addition, the above-mentioned methods are discussed in application areas such as, control and robotics, pattern recognition, medical diagnosis, decision-making, prediction and optimization of complex problems. There are a group of papers with the main theme of type-1, type-2 and type-3 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1, type-2 and type-3 fuzzy logic and their applications. There is also a set of papers that offer theoretical concepts and applications of meta-heuristics in different areas. There are also some papers that present theory and practice of neural networks in different applications. Finally, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas.
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Sugeno Based Fuzzy Systems for Accurate Heart Rate Level Classification.- Interval Type 3 Fuzzy Harmony Search Algorithm for optimizing benchmark functions.- Analysis Comparative of a Mamdani vs Sugeno defuzzification method of a Fuzzy Bee Colony Optimization Algorithm to stable the trajectory in an Autonomous Mobile Robot.- Type 3 Fuzzy Modeling in the Decision of Process for House Purchasing.- Type 3 Fuzzy Modeling of Restaurant Selection Decision Making.- Application of InterCriteria Analysis on the Overall Household Expenditure by Expense Groups.- An Application of InterCriteria Analysis with Self Organizing Map Neural Network.- Momentum Adaptation in Convolutional Neural Networks using a Fuzzy Gravitational Algorithm.- Water Quality Modelling using Multilayer Neural Network and Multivariate Statistical Techniques.- A Generalized net model of Stochastic Gradient Descent combined with Dropout algorithm.- Dropout Prediction for Higher Education Data Sets and Methods, a Brief Overview.- Application of the fireworks algorithm to design a Fuzzy Controller of an Autonomous Mobile Robot.- A Review of Unmanned Aerial Vehicles Using PID Control with Genetic Algorithms and Particle Swarm Optimization.- Comparative Analysis of Continuous and Discrete Mycorrhiza Optimization Algorithms.- Comparative analysis of the performance of the Stochastic Fractal Search and Artificial Gorilla Troops Optimization methods.- Genetic optimization of PID controllers for Unmanned Aerial Vehicles.
