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Proceedings Paper

Study on algorithm of process neural network for soft sensing in sewage disposal system
Author(s): Zaiwen Liu; Hong Xue; Xiaoyi Wang; Bin Yang; Siying Lu
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Paper Abstract

A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

Paper Details

Date Published: 30 October 2006
PDF: 7 pages
Proc. SPIE 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation, 63582D (30 October 2006); doi: 10.1117/12.718037
Show Author Affiliations
Zaiwen Liu, Beijing Technology and Business Univ. (China)
Hong Xue, Beijing Technology and Business Univ. (China)
Xiaoyi Wang, Beijing Technology and Business Univ. (China)
Beijing Institute of Technology (China)
Bin Yang, Beijing Technology and Business Univ. (China)
Siying Lu, Beijing Technology and Business Univ. (China)


Published in SPIE Proceedings Vol. 6358:
Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation
Jiancheng Fang; Zhongyu Wang, Editor(s)

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