نتایج جستجو برای: ga bp

تعداد نتایج: 89676  

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In recent years, many efforts have been made to reduce pollution in compression ignition engines. Dimethyl ether is one of the methods to achieve this goal due to its special properties such as high Cetane number and low pollution. Also, one of the parameters that plays an important role in improving combustion and engine performance is fuel injection pressure. In the present study, a numerical...

Journal: :Machines 2021

High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The error model high-speed spindles can compensate for and improve effectively. In order to confirm high precision model, Beetle antennae search algorithm (BAS) proposed optimize prediction based on BP neural network. Through characteristic experiment,...

Journal: :Neurocomputing 2000
Pedro Ángel Castillo Valdivieso Juan Julián Merelo Guervós Alberto Prieto Víctor Manuel Rivas Santos Gustavo Romero

A general problem in model selection is to obtain the right parameters that make a model "t observed data. For a multilayer perceptron (MLP) trained with back-propagation (BP), this means "nding appropiate layer size and initial weights. This paper proposes a method (G-Prop, genetic backpropagation) that attempts to solve that problem by combining a genetic algorithm (GA) and BP to train MLPs w...

2007
V. Rivas G. Romero

This paper proposes a new version of a method (G-Prop-III, genetic backpropaga-tion) that attempts to solve the problem of nding appropriate initial weights and learning parameters for a single hidden layer Mul-tilayer Perceptron (MLP) by combining a genetic algorithm (GA) and backpropagation (BP). The GA selects the initial weights and the learning rate of the network, and changes the number o...

1999
P. A. Castillo

A general problem in model selection is to obtain the right parameters that make a model fit observed data. For a Multilayer Perceptron (MLP) trained with Backpropagation (BP), this means finding the right hidden layer size, appropriate initial weights and learning parameters. This paper proposes a method (G-Prop-II) that attempts to solve that problem by combining a genetic algorithm (GA) and ...

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