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Modeling of Thermodynamic Properties of Refrigerants Using Artifical Neural Networks & Genetic Algorithm

Thermodynamic analysis of the refrigeration system is very complex because of the thermodynamic properties equations of working fluids;

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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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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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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Refrigeration

refrigeration at room temperature (RTMR); an alternative approach based on artificial neural networks (ANNs) to determine thermodynamic properties;

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Thermodynamische Eigenschaften umweltvertraglicher Kaltemittel / Thermodynamic Properties of Environmentally Acceptable Refrigerants

, comprehensive tables of their thermodynamic properties are presented here for the first time. All tables are based on extensive measurements of high;

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Wavelet Neural Networks

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications;

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Stratified Data Partitioning in Artificial Neural Network

propose a data clustering algorithm to overcome the drawbacks of the reported data partitioning algorithms. Comparisons have been made using three;

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Artificial Neural Networks

these weights are adaptable, as they can be adjusted according to a learning algorithm. The usage of artificial neural networks today;

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Neural Networks in Finance

This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used;

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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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Neural Network Programming with Python

backpropagation algorithm. This is the algorithm behind the functionality of neural networks, and it involves a forward and backward pass. Numby is a;

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Economic Modeling Using Artificial Intelligence Methods

networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi;

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Introduction to Deep Learning and Neural Networks with PythonT

gradient descent algorithm to manually perform all calculations in both the forward and backward passes of training a neural network.

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Gas Turbines Modeling, Simulation, and Control

Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the;

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Gas Turbines Modeling, Simulation, and Control

Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the;

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Nonlinear Modeling Analysis and Predistortion Algorithm Research of Radio Frequency Power Amplifiers

modeling (including neural Volterra series modeling, neural network modeling, X-parameter modeling), nonlinear analysis methods, and power;

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Pattern Recognition and Computational Intelligence Techniques Using Matlab

foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for;

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Simulating Neural Networks with Mathematica

with Neural Networks Feedback and Recurrent Networks Adaptive Resonance Theory Genetic Algorithms 020156629XB04062001;

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Modeling Brain Function

of models of neural networks have resulted in discoveries of important parallels between the properties of statistical, nonlinear cooperative;

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Modeling, Simulation, and Optimization of Supercritical and Subcritical Fluid Extraction Processes

, conventional optimization techniques and state-of-the-art genetic algorithm methods. Numerous practical examples and case studies on the application;

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Exploring Neural Networks with C#

you discover the properties of neural networks. Following the procedures and using the programs included with the book will allow you to;

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Recent Progress in Artificial Neural Networks

Artificial neural networks (ANNs) are computing systems that are motivated by the design and functioning of biological neural networks. Its;

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New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks

optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these;

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Exploring Neural Networks with C#

you discover the properties of neural networks.Following the procedures and using the programs included with the book will allow you to learn;

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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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