Results 261 to 270 of about 66,774 (311)

The application of BP neural network in Coal analysis

2011 International Conference on Machine Learning and Cybernetics, 2011
Coal analysis is of great significance to Coal power plant boiler combustion system in the diagnosis and optimization, and Calorific value of coal is an important indicator of coal quality analysis. So the research of the relation among Coal analysis data, elemental analysis data and the calorific is of great significance.
Wan-Ye Yao, Ling Su, Shi Yin
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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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Multiplex communication by BP learning in neural network

2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2016
It is a mystery that neural network composed of neurons with fluctuating characteristics can transmit information well reliably. In this paper, we show, in a simulation using a 9×9 2D mesh neural network, 9 to 1 multiplex communication is possible with 99% correct rate. Neurons are modeled by integrate and fire model without leak.
Shinichi Tamura, Yoshi Nishitani, Chie Hosokawa, Tomomitsu Miyoshi, Hajime Sawai, Yuko Mizuno-Matsumoto, Yen-Wei Chen 0001   +6 more
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A parameter adjustment algorithm of BP neural network

2008 3rd International Conference on Intelligent System and Knowledge Engineering, 2008
BP neural network converges slowly and usually falls into partial minimum points. In this paper a new parameter adjustment algorithm is proposed, using anterior accumulated information to modify momentum. The algorithm has characteristics of enhancing the network convergence rate, preventing vibration and reducing network errors.
Xiaozhong Li, Qiu Li
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An Improved BP Neural Network Algorithm

2020 7th International Conference on Information Science and Control Engineering (ICISCE), 2020
In order to solve the problems of improper learning rate setting and low accuracy caused by over-fitting in traditional BP deep neural network, an improved BP neural network algorithm is proposed. In this algorithm, drop-out mechanism is introduced to prevent neural network from overfitting, and in order to solve the problem of improper learning rate ...
Liu Ya, Xu Zhen
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A Ranging Model Based on BP Neural Network

Intelligent Automation & Soft Computing, 2015
AbstractThe traditional Shadowing model relies too much on parameters and specific environment, so its application occasions in WSN are restricted. This paper studies the wireless signal propagation model and proposes the ranging model based on BP neural network model, it has the ability of autonomous learning according to different environments, and ...
Xiaohui Chen, Mengjiao Zhang, Kai Ruan, Canfeng Gong, Yinyin Zhang, Simon X. Yang   +5 more
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Study of BP neural network based on MECA

2005 IEEE International Conference on Granular Computing, 2005
This paper designs BP neural network with mind evolution clone algorithm (MECA). Taking the relation between diversity of mind evolution population and clone mechanism of biology into account, MECA is proposed in the paper. Not only can the algorithm converge to globally optimal solution, but also it solves premature convergence problem efficiently ...
Hongbo Guo, Gang Xie 0001, Zehua Chen 0001, Keming Xie   +3 more
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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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BP Neural Network Sensitivity Analysis and Application

2010
BP neural network as a data-mining technique can be used to factor analysis, but multi-layer BP neural network with hidden layer and between layers of neurons connected by weights staggered, so input variables on output variables. The size of impact is not intuitive.
Jianhui Wu 0003, Gouli Wang, Sufeng Yin, Liqun Yu   +3 more
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Hardware Trojans detection based on BP neural network

2020 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA), 2020
This paper uses side channel analysis to detect hardware Trojan based on back propagation neural network. First, a power consumption collection platform is built to collect power waveforms, and the amplifier is utilized to amplify power consumption information to improve the detection accuracy.
Lan Xu, Jianwei Li, Li Dai, Ningmei Yu
openaire   +1 more source