Empirical Analysis of the Assessment of Computer Laboratory Management Based on BP Network Model

2011 ◽  
Author(s):  
Li Jun-qing ◽  
Wei Ying-bing ◽  
Cai Mei ◽  
Huang Hao ◽  
Chen Yi-zhuo
Keyword(s):  
Empirical Analysis ◽  
Network Model ◽  
Laboratory Management ◽  
Bp Network ◽  
Computer Laboratory

A Novel Quantum Neural Network Model with Variable Selection for Short Term Load Forecasting

2010 ◽  
Vol 20-23 ◽  
pp. 612-617 ◽  
Author(s):  
Wei Sun ◽  
Yu Jun He ◽  
Ming Meng
Keyword(s):  
Neural Network ◽  
Variable Selection ◽  
Network Model ◽  
Neural Network Model ◽  
Load Forecasting ◽  
Short Term ◽  
Bp Network ◽  
Quantum Neural Network ◽  
Short Term Load Forecasting ◽  
Selection For

The paper presents a novel quantum neural network (QNN) model with variable selection for short term load forecasting. In the proposed QNN model, first, the combiniation of maximum conditonal entropy theory and principal component analysis method is used to select main influential factors with maximum correlation degree to power load index, thus getting effective input variables set. Then the quantum neural network forecating model is constructed. The proposed QNN forecastig model is tested for certain province load data. The experiments and the performance with QNN neural network model are given, and the results showed the method could provide a satisfactory improvement of the forecasting accuracy compared with traditional BP network model.

A Brief Analysis on Computer Laboratory Management in High Schools

2011 ◽  
Vol 187 ◽  
pp. 540-543
Author(s):  
Wei Ming Gao ◽  
Min Liu ◽  
Ya Qin Wang ◽  
Li Mei Liu
Keyword(s):  
High School ◽  
High Schools ◽  
Economic Benefits ◽  
Laboratory Management ◽  
Computer Laboratory ◽  
Vital Part

The computer labotory management in high schools is a vital part in the management of university. In order to take good advantage of computer labotory in high school so as to carry out smooth work on teaching and doing experiments and create the greatest social and economic benefits, it is essential to standardize the management of computer labotory in high schools in a scientific way.

scholarly journals Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Dongge Cui ◽  
Chuanqu Zhu ◽  
Qingfeng Li ◽  
Qiyun Huang ◽  
Qi Luo
Keyword(s):  
Network Model ◽  
Network Models ◽  
Particle Swarm Algorithm ◽  
Neural Network Models ◽  
Foundation Pit ◽  
Bp Network ◽  
Deformation Prediction ◽  
Application Range ◽  
Limited Applicability ◽  
Bp Model

Deformation prediction is significant to the safety of foundation pits. Against with low accuracy and limited applicability of a single model in forecasting, a PSO-GM-BP model was established, which used the PSO optimization algorithm to optimize and improve the GM (1, 1) model and the BP network model, respectively. Combining a small amount of measured data during the excavation of a bottomless foundation pit in a Changsha subway station, the calculations based on the PSO-GM model, the PSO-BP network model, and the PSO-GM-BP model compared. The results show that both the GM (1, 1) and BP neural network models can predict accurate results. The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. Due to its reliable accuracy and wide application range, the PSO-GM-BP model can effectively guide the construction of foundation pits, and it also has certain reference significance for other engineering applications.

Research of the System Based on BP Network for the Prediction of Grape Disease

2013 ◽  
Vol 462-463 ◽  
pp. 476-480
Author(s):  
Feng Bao ◽  
Juan Wang ◽  
Zhen Hui Ren
Keyword(s):  
Influencing Factors ◽  
Network Model ◽  
Network Structure ◽  
Good Effect ◽  
Bp Network ◽  
Disease Occurrence ◽  
Sample Data ◽  
Long Term Prediction ◽  
Selection Of

The text introduced a system based on BP network for the prediction of grape disease. It included the design of a network structure, the selection of parameter for network study, the processing of sample data etc. With the use of BP network model, this system can forecast the extent of grape disease, so it is applicable to the conditions which have many influencing factors, complicated relationship, difficulty of analyze quantitatively and requirement of long-term prediction. Using this system to the prediction of grape disease in Zhuo Lu area Zhang Jia Kou city, the authors obtained a good effect, which is of value to the prediction of grape disease occurrence.

Management System of Computer Laboratory in Liberal College

2013 ◽  
Vol 411-414 ◽  
pp. 712-715
Author(s):  
Rong Hua Zhang
Keyword(s):  
Web Sites ◽  
Traffic Monitoring ◽  
Remote Access ◽  
Network Technology ◽  
Laboratory Management ◽  
Computer Laboratory ◽  
Room Design ◽  
Actual Use ◽  
The University ◽  
Management Issues

The university network is very popular, the use of computer networks for laboratory management has become a necessity. We proposed the construction of the building room memorandum ideas and some strategies that can be implemented, the better solution normative room management issues. According to the actual use of university computer room design possible combination of VLAN and VPN solutions. We used a more mature support for multiple operating systems and supports SNMP network devices Mrtg tools to help us achieve traffic monitoring, reducing the need for repeat open, traffic monitoring can be a good solution to the problem. Use of virtual LANs, the use of wireless network technology, the use of remote monitoring technology, the use of Web sites and remote access, have made these physical room on the formation of a relatively independent logical connections to facilitate the reunification of management and maintenance.

scholarly journals The Application and Research of the GA-BP Neural Network Algorithm in the MBR Membrane Fouling

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chunqing Li ◽  
Zixiang Yang ◽  
Hongying Yan ◽  
Tao Wang
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Bp Neural Network ◽  
Membrane Fouling ◽  
Sewage Treatment ◽  
Principal Component ◽  
Operating Pressure ◽  
Bp Network ◽  
Factors Affecting ◽  
Membrane Flux

It is one of the important issues in the field of today's sewage treatment of researching the MBR membrane flux prediction for membrane fouling. Firstly this paper used the principal component analysis method to achieve dimensionality and correlation of input variables and obtained the three major factors affecting membrane fouling most obvious: MLSS, total resistance, and operating pressure. Then it used the BP neural network to establish the system model of the MBR intelligent simulation, the relationship between three parameters, and membrane flux characterization of the degree of membrane fouling, because the BP neural network has slow training speed, is sensitive to the initial weights and the threshold, is easy to fall into local minimum points, and so on. So this paper used genetic algorithm to optimize the initial weights and the threshold of BP neural network and established the membrane fouling prediction model based on GA-BP network. As this research had shown, under the same conditions, the BP network model optimized by GA of MBR membrane fouling is better than that not optimized for prediction effect of membrane flux. It demonstrates that the GA-BP network model of MBR membrane fouling is more suitable for simulation of MBR membrane fouling process, comparing with the BP network.

Extending a tourism causality network model: A cross-country, multigroup empirical analysis

2011 ◽  
Vol 11 (4) ◽  
pp. 258-277 ◽  
Author(s):  
Guy Assaker ◽  
Vincenzo Esposito Vinzi ◽  
Peter O’Connor
Keyword(s):  
Empirical Analysis ◽  
Network Model ◽  
Cross Country
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