DocumentCode
466907
Title
Research on Risk Control Model of Cooperatively Technical Innovation based on Wavelet and Nerve Network
Author
Changhui, Yang
Author_Institution
Zhengzhou Univ., Zhengzhou
Volume
1
fYear
2007
fDate
July 30 2007-Aug. 1 2007
Firstpage
591
Lastpage
594
Abstract
Innovation is the impetus and source of enterprise development, and the cooperatively technical innovation is become a main innovation method. It is necessary to take measure to prevent and indemnify the loss that the risk may bring. Because of the existence of the complex non-linear function mechanism between the risk factors, so the non-linear method can be used to research the keeping way and controlling mechanism of cooperatively technical innovation. At first, this paper analyzed the seeking method of enterprise cooperatively technical innovation risk, and the steps of seeking risks are presented. And then the concept of controlling risk regulation gradient is put forward, and the method of calculating risk regulation gradient is expatiated in detail. The nerve network is suitable for recognizing and simulating nonlinear system, and the wavelet transformation or the decomposition displays the good time frequency localization characteristic and the multi-criteria function, therefore the wavelet nerve network based on the wavelet decomposition and the nerve network has the good fault-tolerant ability and the non-linearity approaching performance. And based on this, a complete controlling risk model of cooperatively technical innovation is brought forward, and the algorithm of risk control model is discussed.
Keywords
business data processing; innovation management; neural nets; nonlinear functions; nonlinear systems; risk management; wavelet transforms; complex nonlinear function; cooperatively technical innovation; enterprise development; fault-tolerance; multicriteria function; nonlinear system; risk control model; risk regulation gradient; technical innovation risk; time frequency localization; wavelet decomposition; wavelet nerve network; wavelet transformation; Artificial intelligence; Character recognition; Control systems; Distributed computing; Investments; Loss measurement; Nonlinear systems; Risk analysis; Software engineering; Technological innovation;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
Conference_Location
Qingdao
Print_ISBN
978-0-7695-2909-7
Type
conf
DOI
10.1109/SNPD.2007.55
Filename
4287576
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