Artificial intelligence for cognitive modeling theory and practice
Part A: Artificial Intelligence & Cognitive Computing : Theory &Concept 1. Introduction to AI. 2. Practical Approach of Fuzzy Logic Controller. 3. A Practical Approach to Neural Network Models. 4. Introduction to Genetic Algorithm. 5. Modeling of ANFIS (Adaptive Fuzzy Inference System) Syste...
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| Zusammenfassung: | Part A: Artificial Intelligence & Cognitive Computing : Theory &Concept 1. Introduction to AI. 2. Practical Approach of Fuzzy Logic Controller. 3. A Practical Approach to Neural Network Models. 4. Introduction to Genetic Algorithm. 5. Modeling of ANFIS (Adaptive Fuzzy Inference System) System. 6. Machine Learning Techniques for Cognitive Modeling Part B: Artificial Intelligence & Cognitive Computing : Practices7. Parametric Optimization of N Channel JFET using Bio Inspired Optimization Techniques. 8. AI based Model of Clinical and Epidemiological Factors for COVID19. 9. Fuzzy Logic Based Parametric Optimization Technique of Electro Chemical Discharge Micro-Machining (-CDM) Process during Micro-Channel Cutting on Silica Glass. 10. Study of ANFIS model to Forecast the Average Localization Error (ALE) with Applications to Wireless Sensor Networks (WSN). 11. Performance Estimation of Photovoltaic Cell using Hybrid Genetic Algorithm & Particle Swarm Optimization. 12. Bio inspired Optimization based PID Controller Tuning for a Non-Linear Cylindrical Tank System. 13. A Hybrid Algorithm Based on CSO & PSO for Parametric Optimization of Liquid Flow model. 14. Modelling of Improved Deep Learning Algorithm for Detection of Type 2 Diabetes. 15. Human Activity Recognition (HAR), Prediction & Analysis using Machine Learning This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model.Features:A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB)A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS)Formulation of the nonlinear model like analysis of ANOVA and response surface methodologyVariety of solved problems on ANOVA and RSMCase studies of above mentioned intelligent techniques on the different process control systemsThis book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xxi, 272 Seiten Illustrationen, Diagramme |
| ISBN: | 9781032105703 978-1-032-10570-3 9781032461397 978-1-032-46139-7 |