ASSESSMENT OF SPATIAL MULTI-CRITERIA DECISION-MAKING WITH PROCESS OF THE ARTIFICIAL NEURAL NETWORKS METHOD TO SITE SELECTION OF THE WASTEWATER TREATMENT PLANT (CASE STUDY: QESHM ISLAND)

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FALLAH MAHDI; VAGHARFARD HASSAN; FARAJZADEH MANOUCHEHR; NICK KHESLAT ALI

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Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF ADVANCED BIOLOGICAL AND BIOMEDICAL RESEARCH (IJABBR) Year:2014 | Volume:2 | Issue:6 Page(s): 2061-2066

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Title

ASSESSMENT OF SPATIAL MULTI-CRITERIA DECISION-MAKING WITH PROCESS OF THE ARTIFICIAL NEURAL NETWORKS METHOD TO SITE SELECTION OF THE WASTEWATER TREATMENT PLANT (CASE STUDY: QESHM ISLAND)

Author(s)

FALLAH MAHDI | VAGHARFARD HASSAN | FARAJZADEH MANOUCHEHR | NICK KHESLAT ALI | Issue Writer Certificate

Keywords

WASTEWATER TREATMENT

SITE SELECTION

ANN

QESHM ISLAND

GIS

Abstract

WASTEWATER TREATMENT technology in the cyclic nature of the process that takes a long time. But man tries to rush to their needs with experience and understanding of the natural processes of interaction, and using technology to build their Industrial development is authorized. Sewage treatment reed have been born from the vision of man's increasing need to water daily decreases the natural resources provide. Location of the place is one of the main uses of GIS and GIS Nowadays many ignorant people are familiar with the location. But what is remembered today as the location of the equivalent SITE SELECTION, the order of analysis that will lead to the best place or places to be for a specific user. Therefore, using multiple and very diverse, the various layers of spatial data according to the criteria considered, together are usually the places where the best places are introduced, and the resulting method. This study is the first layer and standards were prepared from different sources of information, then based on the opinions of experts using analytic hierarchy process weight classes, each benchmark was performed. For network training algorithm of back-propagation and a sigmoidal activation function was used, the results indicate that it is a very high correlation coefficient of the neural network was able to identify suitable areas. Finally, about 104 km QESHM ISLAND area were suitable for the construction of WASTEWATER TREATMENT plant that requires ground visits is the expert.

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APA: Copy

FALLAH, MAHDI, VAGHARFARD, HASSAN, FARAJZADEH, MANOUCHEHR, & NICK KHESLAT, ALI. (2014). ASSESSMENT OF SPATIAL MULTI-CRITERIA DECISION-MAKING WITH PROCESS OF THE ARTIFICIAL NEURAL NETWORKS METHOD TO SITE SELECTION OF THE WASTEWATER TREATMENT PLANT (CASE STUDY: QESHM ISLAND). INTERNATIONAL JOURNAL OF ADVANCED BIOLOGICAL AND BIOMEDICAL RESEARCH (IJABBR), 2(6), 2061-2066. SID. https://sid.ir/paper/339050/en

Vancouver: Copy

FALLAH MAHDI, VAGHARFARD HASSAN, FARAJZADEH MANOUCHEHR, NICK KHESLAT ALI. ASSESSMENT OF SPATIAL MULTI-CRITERIA DECISION-MAKING WITH PROCESS OF THE ARTIFICIAL NEURAL NETWORKS METHOD TO SITE SELECTION OF THE WASTEWATER TREATMENT PLANT (CASE STUDY: QESHM ISLAND). INTERNATIONAL JOURNAL OF ADVANCED BIOLOGICAL AND BIOMEDICAL RESEARCH (IJABBR)[Internet]. 2014;2(6):2061-2066. Available from: https://sid.ir/paper/339050/en

IEEE: Copy

MAHDI FALLAH, HASSAN VAGHARFARD, MANOUCHEHR FARAJZADEH, and ALI NICK KHESLAT, “ASSESSMENT OF SPATIAL MULTI-CRITERIA DECISION-MAKING WITH PROCESS OF THE ARTIFICIAL NEURAL NETWORKS METHOD TO SITE SELECTION OF THE WASTEWATER TREATMENT PLANT (CASE STUDY: QESHM ISLAND),” INTERNATIONAL JOURNAL OF ADVANCED BIOLOGICAL AND BIOMEDICAL RESEARCH (IJABBR), vol. 2, no. 6, pp. 2061–2066, 2014, [Online]. Available: https://sid.ir/paper/339050/en

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