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Spatially Explicit Hyperparameter Optimization for Neural Networks

automated spatially explicit hyperparameter optimization approach to identify optimal or near-optimal parameter settings for neural networks in the;

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Evolutionary Machine Learning Techniques

neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer, whale optimization;

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Evolutionary Machine Learning Techniques

types of artificial neural networks, including genetic algorithm, ant colony optimization, particle swarm optimization, grey wolf optimizer;

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TensorFlow for Deep Learning From Linear Regression to Reinforcement Learning

used in thousands of applications Turn prototypes into high-quality models with hyperparameter optimization Process images with;

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Deep Neural Networks and Applications

. Also discussed in the book is the optimization of deep learning for the best performance of e-learning data, the methodology and the research;

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Neural Networks for Optimization and Signal Processing

A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but;

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Evolutionary Algorithms and Neural Networks

optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as;

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Combinatorial Development of Solid Catalytic Materials

optimization and artificial neural networks - are described. The book is unique in that it describes evolutionary optimization in a broader context;

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Simulating Neural Networks with Mathematica

will learn how to simulate neural network operations using Mathematica, and will learn techniques for employing Mathematica to assess neural;

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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning;

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Network Models for Control and Processing

experimentation and physical mechanisms with computer-assisted and hardware models of biological neural networks and neurons; improving processes for;

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Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

Neural networks and neural dynamics are powerful approaches for the online solution of mathematical problems arising in many areas;

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Neural Networks Theory

, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized;

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Neural Information Processing

Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019.For ICONIP 2019 a total of 345 papers was carefully;

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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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Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

We describe in this book, recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid;

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Applications of Artificial Neural Networks for Nonlinear Data

deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature;

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Designs and Applied Principles of Artificial Neural Networks

This book presents a broad overview on the current various design modules and applications of artificial neural systems. Artificial neural;

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Optimization of PID Controllers Using Ant Colony and Genetic Algorithms

Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving;

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Artificial Neural Networks for Renewable Energy Systems and Real-World Applications

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex;

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New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension

combined using fuzzy logic. Finally, two genetic algo-rithms are used to perform the optimization of the modular neural networks parameters and;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Hybrid Intelligent Systems in Control, Pattern Recognition and Medicine

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations;

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Optimization Techniques for Solving Complex Problems

Real-world problems and modern optimization techniques to solve them Here, a team of international experts brings together core ideas for;

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Recurrent Neural Networks

scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized;

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Advances in Neural Networks ISNN 2015

The volume LNCS 9377 constitutes the refereed proceedings of the 12th International Symposium on Neural Networks, ISNN 2015, held in Jeju;

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Computational Intelligence

the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy;

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