Machine Learning for Model Order Reduction, Softcover reprint of the original 1st ed. 2018
Auteur : Mohamed Khaled Salah
- Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction;
- Describes new, hybrid solutions for model order reduction;
- Presents machine learning algorithms in depth, but simply;
- Uses real, industrial applications to verify algorithms.
Chapter1: Introduction.- Chapter2: Bio-Inspired Machine Learning Algorithm: Genetic Algorithm.- Chapter3: Thermo-Inspired Machine Learning Algorithm: Simulated Annealing.- Chapter4: Nature-Inspired Machine Learning Algorithm: Particle Swarm Optimization, Artificial Bee Colony.- Chapter5: Control-Inspired Machine Learning Algorithm: Fuzzy Logic Optimization.- Chapter6: Brain-Inspired Machine Learning Algorithm: Neural Network Optimization.- Chapter7: Comparisons, Hybrid Solutions, Hardware architectures and New Directions.- Chapter8: Conclusions.
Date de parution : 01-2019
Ouvrage de 93 p.
15.5x23.5 cm
Date de parution : 03-2018
Ouvrage de 93 p.
15.5x23.5 cm