Results 271 to 280 of about 66,774 (311)

Competitiveness Evaluation of Port Based on BP Neural Network

2021
To solve the problem of ignoring the influence of intelligent port and green port in the existing evaluation index of port competitiveness, this study introduces some indexes such as the level of port informatization, energy consumption per unit GDP and the output value rate of science and technology input to construction index.
Chongkai Zhang, Jianmin Li, Zhipeng Zhang, Wan Zhang   +3 more
openaire   +1 more source

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
openaire   +1 more source

Edge detection with BP neural networks

ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344), 2002
A new edge detection technique is proposed which makes use of a backpropagation (BP) neural network. We classify the edge patterns in binary images into 18 categories. After training on the pre-defined edge patterns, the neural network is applied to classify any type of edge into one of the 18 categories.
null Zhengquan He, M.Y. Siyal
openaire   +1 more source

Text sentiment classification based on BP neural network

2021 21st ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Winter), 2021
In a consumer-oriented market, people's opinions or comments will, directly or indirectly, have influence on other people's decisions. For example, as choosing goods or online services, positive opinions or comments can promote consumers' purchase. At the same time, negative comments can also reduce consumers' enthusiasm for buying.
Nanchang Cheng, Wenchao Song, Kang Song
openaire   +1 more source

Boundedness of Weight Elimination for BP Neural Networks

2014
Weight elimination can be usefully interpreted as an assumption about the prior distribution of the weights trained in the backpropagation neural networks (BPNN). Weight elimination based on different scaling of weight parameters is of a general form, with the weight decay and subset selection methods as special cases.
Jian Wang 0010, Jacek M. Zurada, Yanjiang Wang 0001, Jing Wang, Guofang Xie   +4 more
openaire   +1 more source

Blink Detection Algorithm Based on BP Neural Network

2020 6th International Conference on Robotics and Artificial Intelligence, 2020
Blinking is a very important behavior feature for fatigue driving detection. It is of great significance to detect the blink times regularly for reducing traffic accidents. Therefore, this paper proposes a blink detection algorithm based on BP neural network algorithm.
Zhenghao Hu, Hao Zhai, Aomei Li, Zhizhong Xi, Zhaozhen Jiang, Beiyao Cui   +5 more
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Application of BP neural network in wireless network security evaluation

2010 IEEE International Conference on Wireless Communications, Networking and Information Security, 2010
As most assessment indices are subjective and uncertainly in wireless network security evaluation, this paper proposes a model that BP neural network is used in wireless network security assessment system. After building a neural network model, we could obtain the values of each evaluation index and the whole risk situation of the wireless network by ...
Jianxin Fu, Lianfen Huang, Yan Yao
openaire   +1 more source

A Low-complexity Neural BP Decoder with Network Pruning

2020 International Conference on Information and Communication Technology Convergence (ICTC), 2020
Existing deep learning-based channel decoders, called neural decoders, suffer from demands on an excessively high computational complexity and large memory resource. In this work, we will show that a low-complexity neural belief propagation (BP) decoder can be constructed by utilizing the network pruning technique.
Seokju Han, Jeongseok Ha
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The Application of the BP Neural Network in the Nonlinear Optimization

2010
In this paper, a hybrid algorithm is proposed which combines the conjugate gradient theory with BP network algorithm. The algorithm regards the overall average error of neural network as the objective function, and the seeking weights and thresholds of the neural network as the design variables.
Chunsheng Dong, Liu Dong, Mingming Yang
openaire   +1 more source

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
openaire   +1 more source