The evaluation of renewable energy power using hybrid model of neural network and data envelopment analysis (neuro - DEA)
Publish place: International Journal of Applied Research on Industrial Engineering، Vol: 1، Issue: 1
Publish Year: 1393
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJARIE-1-1_001
تاریخ نمایه سازی: 26 اردیبهشت 1394
Abstract:
Energy is essential parameter for economic – social development and quality of life. Sustainable energy is requisite for any economic growth. Nowadays, new options for producing energyand using technologies for its production are reproducible. So, the choice of technology is very important. In this article, 6 different renewable powers has evaluated using Hybrid model of Artificial-Neural Network (ANN) and data envelopment analysis base on economic- technical indicators. Because, the low number of inputs and outputs of decision making units, (DMUs), leading to a reduction a separable power of DMUs at traditional DEA, so the NEURO-DEA was used the simulation results shows that off-shore wind energy have high efficiency rather than other studied energy
Keywords:
Data Envelopment Analysis (DEA) Artificial-Neural Network (ANN)
Authors
Fershteh Poorahangaryan
Faculty of engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran.
Ali Shahbi
Faculty of engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran
Esmaeel Nabiee
Faculty of engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran.