Determine of weight environmental indicator in IMDPA model by Artificial Neural Network

سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 475

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شناسه ملی سند علمی:

ICDAT01_380

تاریخ نمایه سازی: 12 تیر 1395

چکیده مقاله:

Iranian Desertification Model potential Assessment (IMDPA), it is a model for studies and assess desertification in Iran .In this model, a lot of indicators and criteria considered.Indicators of Climate, Geology, Geomorphology, Soil, VegetationCover, Agriculture, Water andErosion are the most important environmental factors fordesertification assessment in Iran.Artificial neural networks (ANN) the idea is to process information that inspired by biological nervous system such as the brain to process information. Environmental indicatorsfor assessing the severity of desertification have more different criteria with unknown different weights. Result of this research show Neural Networks and Genetic Algorithms can be used to optimize environmental indicators and exact weight of it in this model.

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نویسندگان

Ali Reza Nejadmohammd Namaghi

PhD Student of Tehran University, Mashhad, Iran,

G. R. Zehtabian

Faculty professor at Tehran University, Iran

A. R. Moghadam Nia

Faculty professor at Tehran University, Iran

H Azarnivand

Faculty professor at Tehran University, Iran