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
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Journal ArticleDOI
Defect Detection Method of Carbon Fiber Sucker Rod Based on Multi-Sensor Information Fusion and DBN Model
TL;DR: In this article , a defect detection method based on multi-sensor information fusion and a deep belief network (DBN) model was proposed to identify carbon fiber sucker rods in online and full-coverage scanning.
Journal ArticleDOI
A Comparative Study of a Fully-Connected Artificial Neural Network and a Convolutional Neural Network in Predicting Bridge Maintenance Costs
TL;DR: In this article , a bridge maintenance cost prediction model was developed using a fully-connected artificial neural network (ANN) and convolutional neural network(CNN) respectively, and the results from the two models were compared and their prediction accuracies were analyzed.
Journal ArticleDOI
A Multi-Axis Synchronization Control Approach Based on Adjacent Cross-Coupling Strategy
TL;DR: The multi-axis cross-coupled control approach based on BP neural networks is applied to a three-axis synchronization control system and its effectiveness is discussed, showing that this method can effectively obtain the synchronization with a quick convergence.
Journal ArticleDOI
Auto station precipitation data making up using an improved neuro net
Jing Lu,Xiakun Zhang +1 more
TL;DR: This paper proposes a “from coarse to fine” (FCTF) neural network to fill out the missing blanks and experiments show that this method to solve the problem of meteorological data shortage is effective.
Journal ArticleDOI
Harris hawks optimization algorithm and BP neural network for ultra-wideband indoor positioning.
TL;DR: The results show that the predicted trajectory of the HHO and BPNN hybrid algorithm (HHO-BP) matches the actual position in the two-dimensional localization scenario with four base stations; the optimized average positioning error is effectively reduced in both indoor LOS and NLOS environments.
References
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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.
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Evolving artificial neural network ensembles
Xin Yao,Md. Monirul Islam +1 more
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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.
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