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Optinformatics in Evolutionary Learning and Optimization

This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and;

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Optinformatics in Evolutionary Learning and Optimization

This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and;

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Evolutionary Learning

evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due;

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Advances in Learning Automata and Intelligent Optimization

. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning;

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Evolutionary Multi-Criterion Optimization

optimization; multi-modal optimization; many-objective optimization; performance evaluations and empirical studies; EMO and machine learning; surrogate;

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Data-Driven Evolutionary Optimization

seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms;

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Artificial Intelligence Algorithms and Applications

topical sections: new frontier in evolutionary algorithms; evolutionary multi-objective and dynamic optimization; intelligent multimedia systems;

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Artificial Evolution

Dynamics, Theory, Algorithmics and Modeling, Implementations, Application of Evolutionary Paradigms to the Real World, Dynamic Optimization;

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Evolutionary Programming IV

in Evolutionary Optimization Pattern Discovery, Pattern Recognition, and System Identification.- Hierarchical Levels of Learning.- Self-Adaptation;

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Evolutionary Multi-Objective System Design

of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods;

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Evolutionary Multi-Objective System Design

of the optimization process. Multi-objective optimization methods can be subdivided into classical and evolutionary. The classical methods;

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Artificial Evolution

papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co;

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Classical and Evolutionary Algorithms in the Optimization of Optical Systems

Classical and Evolutionary Algorithms in the Optimization of Optical Systems presents research results in the field of classical and;

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A Brief Introduction to Continuous Evolutionary Optimization

Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the;

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Evolutionary Machine Learning Techniques

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded;

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Evolutionary Machine Learning Techniques

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded;

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Parallel Problem Solving from Nature -- PPSN XIV

optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization;

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Evolutionary Algorithms

described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches;

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Artificial Evolution

papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co;

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Advances in Swarm and Computational Intelligence

; evolutionary and genetic algorithms; differential evolution; brain storm optimization algorithm; biogeography based optimization; cuckoo search; hybrid;

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Advances in Swarm and Computational Intelligence

; evolutionary and genetic algorithms; differential evolution; brain storm optimization algorithm; biogeography based optimization; cuckoo search; hybrid;

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Advances in Swarm and Computational Intelligence

; evolutionary and genetic algorithms; differential evolution; brain storm optimization algorithm; biogeography based optimization; cuckoo search; hybrid;

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Advances in Swarm Intelligence

Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks;

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Advances in Swarm Intelligence

algorithm; bacterial foraging optimization; genetic algorithm and evolutionary computation; multi-objective optimization; machine learning; data;

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Parallel Problem Solving from Nature PPSN XVI

artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world;

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Parallel Problem Solving from Nature PPSN XVI

artificial intelligence; genetic and evolutionary algorithms; genetic programming; landscape analysis; multiobjective optimization; real-world;

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Intelligent System Applications In Power Engineering

This text on evolutionary computation presents an account of neural network and evolutionary programming applications as optimization;

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