DocumentCode
1861804
Title
A Novel FNN Algorithm and Its Application in FCC Evaluation Based on Kirkpatrick Model
Author
Zhang, Yanqing
Author_Institution
Econ. & Manage. Dept., Jiyuan Vocational & Tech. Coll., Jiyuan, China
fYear
2010
fDate
9-10 Jan. 2010
Firstpage
447
Lastpage
450
Abstract
For a long time, the necessary funds of entire electric power industry is fully funded by the government or mandatory financial loans due to the monopoly of the electric power industry and the government acts, and which results in the research on the electric power enterprise financing credit capacity (FCC) evaluation is lacking. The financing capacity is influenced by many factors, including the qualitative indicators and quantitative indices, this paper overcomes the shortcoming of tradition linear evaluation methods of financing credit capacity, proposes a measuring method which establishes a capacity evaluation system combined with Kirkpatrick model and describes the evaluation mechanism based on fuzzy neural network (FNN) algorithm. The capacity evaluation of 10 enterprises shows that the results given by this model are reliable, and this method to evaluate the financing credit capacity is feasible.
Keywords
credit transactions; electrical products industry; financial management; fuzzy neural nets; FCC evaluation; FNN algorithm; Kirkpatrick model; capacity evaluation system; electric power enterprise financing credit capacity; electric power industry; fuzzy neural network algorithm; linear evaluation methods; qualitative indicators; quantitative indices; Energy management; FCC; Financial management; Fuzzy neural networks; Industrial economics; Local government; Marketing and sales; Mining industry; Power generation economics; Power system modeling; FNN algorithm; Kirkpatrick model; comprehensive evaluation; financing credit capacity;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location
Phuket
Print_ISBN
978-1-4244-5397-9
Electronic_ISBN
978-1-4244-5398-6
Type
conf
DOI
10.1109/WKDD.2010.33
Filename
5432544
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