Journal ArticleDOI
An optimizing BP neural network algorithm based on genetic algorithm
TLDR
A method that combines GA and BP to train the neural network works better; is less easily stuck in a local minimum; the trained network has a better generalization ability; and it has a good stabilization performance.Abstract:
A back-propagation (BP) neural network has good self-learning, self-adapting and generalization ability, but it may easily get stuck in a local minimum, and has a poor rate of convergence. Therefore, a method to optimize a BP algorithm based on a genetic algorithm (GA) is proposed to speed the training of BP, and to overcome BP's disadvantage of being easily stuck in a local minimum. The UCI data set is used here for experimental analysis and the experimental result shows that, compared with the BP algorithm and a method that only uses GA to learn the connection weights, our method that combines GA and BP to train the neural network works better; is less easily stuck in a local minimum; the trained network has a better generalization ability; and it has a good stabilization performance.read more
Citations
More filters
Journal ArticleDOI
Stability analysis of underground mine hard rock pillars via combination of finite difference methods, neural networks, and Monte Carlo simulation techniques
TL;DR: In this paper, the authors considered the geological strength index (GSI) of hard rock pillars as a new variable for predictive purposes, which was developed by combining numerical simulation software (i.e., FLAC3D) and a backpropagation neural network.
Journal ArticleDOI
Review of Data Fusion Methods for Real-Time and Multi-Sensor Traffic Flow Analysis
Shafiza Ariffin Kashinath,Salama A. Mostafa,Aida Mustapha,Hairulnizam Mahdin,David Lim,Moamin A. Mahmoud,Mazin Abed Mohammed,Bander Ali Saleh Al-rimy,Mohd Farhan Md Fudzee,Tan Jhon Yang +9 more
TL;DR: In this article, the authors present a review of data fusion methods used for real-time and multi-sensor (heterogeneous) traffic flow analysis in intelligent transportation systems (ITS) and propose a guideline of constructing DF methods which involve preprocessing, filtering, decision, and evaluation as core steps.
Journal ArticleDOI
Empirical Mode Decomposition based Multi-objective Deep Belief Network for short-term power load forecasting
TL;DR: This paper proposes an Empirical Mode Decomposition Based Multi-objective Deep Belief Network prediction method (EMD-MODBN), which has obvious advantages in prediction accuracy and generalization ability.
Journal ArticleDOI
Towards a Trust Prediction Framework for Cloud Services Based on PSO-Driven Neural Network
TL;DR: In the proposed hybrid prediction algorithm named PSO-NN, particle swarm optimization (PSO) is introduced to enhance NN by optimizing its initial settings, and significantly outperforms the basic NN in the terms of prediction precision.
Journal ArticleDOI
Risk assessment of knowledge fusion in an innovation ecosystem based on a GA-BP neural network
TL;DR: The comparison shows that the GA-BP neural network has faster convergence speed and higher stability, can achieve the goal more often, and reduces the possibility of the BP neural network falling into a local optimum instead of reaching global optimization.
References
More filters
Journal ArticleDOI
Evolving artificial neural networks
TL;DR: It is shown, through a considerably large literature review, that combinations between ANNs and EAs can lead to significantly better intelligent systems than relying on ANNs or EAs alone.
Journal ArticleDOI
Comparing backpropagation with a genetic algorithm for neural network training
TL;DR: It is shown that the use of a genetic algorithm can provide better results for training a feedforward neural network than the traditional techniques of backpropagation.
Journal ArticleDOI
Evolving artificial neural network ensembles
Xin Yao,Md. Monirul Islam +1 more
TL;DR: This paper will review some of the recent work in evolutionary approaches to designing ANN ensembles and reveal that there is a deep underlying connection between evolutionary computation and ANNEnsembles.
Journal ArticleDOI
A review of genetic algorithms applied to training radial basis function networks
C. Harpham,W. Dawson,R. Brown +2 more
TL;DR: A brief overview of feedforward ANNs and GAs is given followed by a review of the current state of research in applying evolutionary techniques to training RBF networks.
Journal ArticleDOI
Optimum design of structures by an improved genetic algorithm using neural networks
Eysa Salajegheh,Saeed Gholizadeh +1 more
TL;DR: Using neural networks within the framework of VSP creates a robust tool for optimum design of structures and reduces the computational cost of standard GA.
Related Papers (5)
Learning representations by back-propagating errors
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more