Results 231 to 240 of about 181,909 (270)

On PSO Based BP Neural Network

Applied Mechanics and Materials, 2014
Particle swarm optimization (PSO) based BP neural network is introduced , which is superior to the traditional BP neural network . The traditional BP neural network and PSO algorithm is illustrated respectively, and introduces how to apply PSO algorithm in BP neural network.
Peng Hu, Xiao Quan Song
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Network on Chip architecture for BP neural network

2008 International Conference on Communications, Circuits and Systems, 2008
Recently, networks-on-chips (NoCs) have a great development and have been proposed as a promising solution to complex on-chip communication problems. One of the problems is an application of artificial neural networks (ANNs). In this paper, we propose NoCs for the ANNs. NoCs is designed to implement a BP-ANNs (back-propagation) and evaluated by network-
null Yiping Dong, null Takahiro Watanabe
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Research on Improved BP Learning Algorithm of BP Neural Network

Advanced Materials Research, 2013
Aiming at the existence of the BP neural network learning algorithm in the slow learning speed, the possibility of failure is large, poor generalization ability, there are multiple issues, extreme value point and network structure are difficult to determine, in this paper, we study algorithm improvement methods.
Jian Li Chu, Hong Yan Li, Xiao Ji Chen
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BP-Neural Network for Business Administration

2021
With the further deepening of education reform in our country, it has become an important task to adopt new teaching methods to cultivate talents needed by the market. In order to effectively improve the effect of business administration teaching, teachers should actively explore the importance and practical application process of applying simulation ...
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A New Improved BP Neural Network Algorithm

2009 Second International Conference on Intelligent Computation Technology and Automation, 2009
Neural network is widely used in pattern recognition, image processing and system control. BP neural network has its inherent deficiencies. Its convergence rate is slow. It is easy to fall into the local minimum and the structure of the neural network is hard to determine.
Li Xiaoyuan, Qi Bin, Wang Lu
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Credit decision based on BP neural network

Academic Journal of Business & Management, 2021
The BP neural network model is used to predict the credit records of enterprises without credit records, and the training data set is the relevant data of 123 enterprises with credit records in Appendix 1. Then, on the basis of question 1, it is given that the total annual credit is 100 million yuan, so the loan amount allocated to each enterprise can ...
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Saliency detection based on BP-neural Network

2016 12th World Congress on Intelligent Control and Automation (WCICA), 2016
Saliency detection has a significant influence on improving image analysis and processing techniques. We propose a novel saliency detection method based on BP-neural Network in this paper. First, we need to segment images into superpixels by the SLIC approach. Secondly, from these superpixels, we extract 10-dimensional feature to describe a superpixel.
Pan Duan, Bei Hu, Haiying Sun, Qichang Duan   +3 more
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Interpretable neural networks with BP-SOM

1998
Artificial Neural Networks (ANNS) are used successfully in industry and commerce. This is not surprising since neural networks are especially competitive for complex tasks for which insufficient domain-specific knowledge is available. However, interpretation of models induced by ANNS is often extremely difficult.
Weijters, A.J.M.M., Bosch, van den, A.P.J.   +1 more
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BP NEURAL NETWORK-BASED EFFECTIVE FAULT LOCALIZATION

International Journal of Software Engineering and Knowledge Engineering, 2009
In program debugging, fault localization identifies the exact locations of program faults. Finding these faults using an ad-hoc approach or based only on programmers' intuitive guesswork can be very time consuming. A better way is to use a well-justified method, supported by case studies for its effectiveness, to automatically identify and prioritize ...
W. ERIC WONG, YU QI
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An APSO optimized BP neural network

2011 International Conference on Electronics, Communications and Control (ICECC), 2011
In this paper, the limitations of conventional BP algorithm was analyzed, and to fasten the learning velocity of neural network and enhance its generalization capability, the APSO (adaptive particle swarm optimization) algorithm was introduced into BP network for the optimization of its weights and thresholds.
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