DocumentCode :
3370871
Title :
Fuzzy RBF assessment on productive efficiency of environmental impacted enterprise
Author :
Fengrong, Zhang ; Fet, Annik Magerholn ; Jing, Wang
Author_Institution :
Norwegian Univ. of Sci. & Technol., Trondheim, Norway
fYear :
2009
fDate :
9-12 Aug. 2009
Firstpage :
465
Lastpage :
470
Abstract :
The enterprise development pattern at the cost of environment has been questioned constantly. In people´s opinion, the enterprise should be responsible for social and environmental responsibility, and should bring environmental impacted target into the assessment of productive efficiency. In connection with the issue of assessment on environment impacting production efficiency, this paper divides assessment target into three levels such as input, output and emission, utilizing fuzzy theory and RBF network technology to establish the model for the assessment on the environment impacting production efficiency, and using empirical examples to make network training and assessment. Through comparing BP neural network model and DEA assessment model, it is found that the assessment method combining fuzzy theory with RBF network has obvious advantage and feasibility of fast constringency and undivergent primary simulated value.
Keywords :
environmental management; fuzzy set theory; production engineering computing; radial basis function networks; emission level; environmental impacted enterprise; environmental responsibility; fuzzy RBF assessment; fuzzy theory; input level; output level; productive efficiency; radial basis function networks; social responsibility; Costs; Fuzzy neural networks; Neural networks; Production; Radial basis function networks; Environmental Affect; Fuzzy Theory; Matching figure; RBF Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
Type :
conf
DOI :
10.1109/ICMA.2009.5246593
Filename :
5246593
Link To Document :
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