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)

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.

Authors and Affiliations

Mahdi Fallah| Graduate student GIS and Remote Sensing, University of Hormozgan, Qeshm, Iran, Hassan Vagharfard | Assistant Professor, Department of Natural Resources, University of Hormozgan, Bandar Abbas, Iran, Manouchehr Farajzadeh| Associate Professor, Department of GIS and Rs, University of Tarbiat Modarres, Tehran, Iran, Ali Nick kheslat| Master of water and wastewater, utility company of Qeshm, Qeshm, Iran

Keywords

Related Articles

Identification and characterization of a Pb, Cu and antibiotic resistant bacteria from soil of industrial wastewater ground

Industrial effluents consist many pollutant and heavy metals. Bacteria isolated from industrial west water ground may have potential to tolerate heavy metal. In this study we isolate a Citrobacter sp. which can resist h...

Genetic Diversity of Phytophthora Sojae in Iran

Objective: The aim of this study was to estimate genetic diversity and morphological relationships of Phytophthora sojae from Iran. Methods: During 2005ñ2007, 142 isolates of P. sojae were collected from soil samples...

Effects Drought, Cytokinin and GA3 on Seedling Growth of Basil (Ocimum basilicum)

Priming is one of the seed enhancement methods that might be resulted in increased seed performance (germination and emergence), seedling growth and plant yield under stress conditions, such as salinity, temperature an...

Antimicrobial ‌in Vitro and in Vivo Potential of Five Lichen Species on Fusarium Equiseti and Pectobacterium Carotovora Pv. Carotovora Causal Agents of Potato Rots

Potato is one of the main crops which is suffering from the great losses in storage and the most conventional method of its tuber rot is using hazardous chemicals. Using antimicrobial potential of lichens can be one of t...

The Allopathic Effects of Cyperus Rotundus Extract on the Germination of Lycopersicon esculentum L. var Chef Flat

This experiment was conducted to determine allopathic effects of Cyperus rotundus extracts on the tomato germination. It was a completely randomized design (CRD) with four replications, carried out in the laboratory of...

Download PDF file
  • EP ID EP13296
  • DOI -
  • Views 320
  • Downloads 14

How To Cite

Mahdi Fallah, Hassan Vagharfard, Manouchehr Farajzadeh, Ali Nick kheslat (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, 2(6), 2061-2066. https://europub.co.uk/articles/-A-13296