Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on th...

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Other Authors: Quiroz, Marcela (Editor), Schütze, Oliver (Editor), Ruiz, Juan Gabriel (Editor), de la Fraga, Luis Gerardo (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
VCO
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications. 
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650 7 |a Research & information: general  |2 bicssc 
650 7 |a Mathematics & science  |2 bicssc 
653 |a robust optimization 
653 |a differential evolution 
653 |a ROOT 
653 |a optimization framework 
653 |a drainage rehabilitation 
653 |a overflooding 
653 |a pipe breaking 
653 |a VCO 
653 |a CMOS differential pair 
653 |a PVT variations 
653 |a Monte Carlo analysis 
653 |a multi-objective optimization 
653 |a Pareto Tracer 
653 |a continuation 
653 |a constraint handling 
653 |a surrogate modeling 
653 |a multiobjective optimization 
653 |a evolutionary algorithms 
653 |a kriging method 
653 |a ensemble method 
653 |a adaptive algorithm 
653 |a liquid storage tanks 
653 |a base excitation 
653 |a artificial intelligence 
653 |a Multi-Gene Genetic Programming 
653 |a computational fluid dynamics 
653 |a finite volume method 
653 |a JSSP 
653 |a CMOSA 
653 |a CMOTA 
653 |a chaotic perturbation 
653 |a fixed point arithmetic 
653 |a FP16 
653 |a pseudo random number generator 
653 |a incorporation of preferences 
653 |a multi-criteria classification 
653 |a decision-making process 
653 |a multi-objective evolutionary optimization 
653 |a outranking relationships 
653 |a decision maker profile 
653 |a profile assessment 
653 |a region of interest approximation 
653 |a optimization using preferences 
653 |a hybrid evolutionary approach 
653 |a forecasting 
653 |a Convolutional Neural Network 
653 |a LSTM 
653 |a COVID-19 
653 |a deep learning 
653 |a trust region methods 
653 |a multiobjective descent 
653 |a derivative-free optimization 
653 |a radial basis functions 
653 |a fully linear models 
653 |a decision making process 
653 |a cognitive tasks 
653 |a recommender system 
653 |a project portfolio selection problem 
653 |a usability evaluation 
653 |a multi-objective portfolio optimization problem 
653 |a trapezoidal fuzzy numbers 
653 |a density estimators 
653 |a steady state algorithms 
653 |a protein structure prediction 
653 |a Hybrid Simulated Annealing 
653 |a Template-Based Modeling 
653 |a structural biology 
653 |a Metropolis 
653 |a optimization 
653 |a linear programming 
653 |a energy central 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/76746  |7 0  |z DOAB: description of the publication