Application of Combined Matlab and VB Model in Water Pollution Control Planning

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Abstract:

In order to visualize the water control planning, optimization of Matlab is embeded into VB programe. Friendly man-machine interface can easily realize the integration of data analysis and water pollution control optimization which can form the visualization software related to water pollution control programs. Examples are shown that combination of the two programmes can greatly enhance the grade and accuracy of planning to improve the work efficiency. The potential applications of the combination of VB and Matlab are discussed in final discussion.

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Key Engineering Materials (Volumes 439-440)

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407-410

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June 2010

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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[1] Chen T, Chen H. Approximation capability to functions of several variables, nonlinear functions and operator by radial basis function neural network[J]. IEEE Trans on neural networks, 1995, (6).

DOI: 10.1109/72.392252

Google Scholar

[2] Martin T. Hagan, Howard B. Demuth, Mark H. Beale, Neural network design, China Machine Press, Beijing, (2004).

Google Scholar

[3] L.M. Zhao, H.Y. Hu, D.H. Wei, S.Q. Wang, Multilayer forward artificial neural network, Yellow River Conservancy Press, Zhengzhou, (1999).

Google Scholar

[4] Fu Yongfeng, Zhang jian , Luo Guangming. Application of BP network to groundwater quality evaluation[J]. Journal of Northwest Sci-Tech University Agri. And Fore. 2004, 32(11): 129-132.

Google Scholar

[5] Luo Dinggui, Guo Qing, Wang Xuejun. Neural network model design of surface water environmental quality assessment[J]. Geography and Geo-Information Science, 2003, 19 (5): 77-81 (in Chinese).

Google Scholar

[6] Zhu Changjun, Li wenyao, Zhang pu. Application of Artificial Neural network in water environment quality assessment[J]. Industrial Safety and Environmental Protection, 2005, 31(2): 27-29.

Google Scholar

[7] X. Yuan, H. Li, S. Liu, and G. Cui, Nerve network and heredity algorithm in water scientific domain application, Water Power Press Beijing, China, pp.15-16. (2002).

Google Scholar

[8] Feisi Research and Development Center of Science and Technology, MATAB 6. 5 auxiliary neural network analysis and design, Electronics industry press, Beijing, (2003).

Google Scholar

[9] X.P. Cao, C.H. Hu, Fault prediction for inertial device based on LMBP neural network, Electronics Optic and Control, 2005, 12(6), pp.38-41.

Google Scholar

[10] Cheng Wanli, Li Yifang, Hao Fuqin. The Evaluation of Water Quality of Sanmenxia Reach Based on Fuzzy Math [J]. Environmental Science and management, 2007, 32 (10): 188-190. Input of data Transmit data to Matlab Completion the optimized calculation Back to the calculated results, output of results in VB interface.

Google Scholar