Fuzzy Environmental Model for Evaluating Water Quality of Sangam Zone during Maha Kumbh 2013

It is a well-known fact that water is the basic need of human beings. The industrial wastes nearby rivers and several anthropogenic activities are responsible for deteriorating water quality of rivers in India. The present research paper deals with the design and development of soft computing system to assess the water quality of rivers Ganga and Yamuna during the Maha Kumbh 2013 in and around Sangam Zone, Allahabad, by making use of physicochemical parameters relationship

Fuzzy expert system for drinking water quality index

The role of water in human life is significant as it plays a very essential role in the procedure of human body. Fuzzy logic provides an efficient and useful device for classifying drinking water quality based on limited observations. In this study, a Fuzzy Drinking Water Quality Index (FDWQI) is proposed for evaluation of water quality for drinking purpose. Fuzzy expert system makes it possible to combine the certainty levels for the acceptability of water based on an approved parameter

Using Fuzzy Set Approaches in a Raster GIS for Land Suitability Assessment at a Regional Scale: Case Study in Maros Region, Indonesia

Recently, spatial data on land resources have become more available, detailed, and sophisticated. Accordingly, it requires a method that could deal with those complex and detailed data in an effective way. A fuzzy set method with the semantic import model (SIM) was utilized within a raster GIS (geographic information systems) to analyze the area of Maros Regency on a reconnaissance scale basis. In this study, land attribute values were converted into continuous values (ranging from 0 to 1.0), according to the class limit determined based on field experiences, results of experiments, or fixed conventional standards. The evaluation criteria were based on land attributes which are divided into two main components: soil profile and topography. Each of land attributes within each component was valued from 0 (minimum) to 1.0 (maximum) according to the suitability of maize. Those values were represented as membership values, also ranging from 0 to 1.0. The result from land suitability analysis in Maros Regency for maize cultivation indicates that around 25% of land areas have a land suitability index (LSI) value of above 0.70 (suitable and very suitable), about 11% fall between 0.50 and 0.70 (moderately suitable), and 63% under 0.5 (not suitable). The main limiting factor for maize cultivation in this region is topography, especially slope gradient (s)

Water quality index using fuzzy logic Utcubamba River, Peru

Water is a fundamental nutrient in the life of any living being. Therefore, it is necessary to estimate its quality, because it is an issue of increasing concern countries around the world for reasons such as the health of the population, regional, national and international economic development, and the environmental quality of the ecosystems. One tool that has been used to know the state of the water is the water quality indexes (WQI). The objective of this research was to develop a WQI based on fuzzy logic, which allows for the estimation of water quality in the Utcubamba River. The methodology used was proposed by Icaga in 2007. To evaluate the proposed WQI called "Diffuse Water Quality Index" (DWQI), sixteen points from the sampling conducted by the Research Institute for Sustainable Development during October 2014 on the Utcubamba River and its tributaries were used. To validate the index, it was necessary to estimate the correlation coefficient R2 between the results obtained and those of the NSF WQI wáter quality index reported by the Water Research Center. This new index presented results and reasonable correlation, R2 = 0.81. It is concluded that DWQI can be used as a tool for decision making in the water management of the Utcubamba River

Artificial neural network to estimate an index of water quality

The artificial neural network (RNA) is a computational model that emulates the biological neural system in information processing. The originating models are suitable for the purpose of describing long-term specifics, in addition to nonlinear relationships. This tool is used to predict physical chemical and microbiological parameters that influence water quality. The United States National Sanitation Foundation proposed a water quality index, known as the NSF WQI. This article describes the design, training and use of the three-layer neural perceptron neural model for the calculation of the NSF WQI of the Utcubamba River and its tributaries. Using the Matlab software and applying the Levenberg-Marquardt training algorithm, the optimal RNA architecture was found to be 6-12-1, plus the percentage for the training, validation, and test sets of 70 %, 10 %, and 20 % respectively. RNA performance has been evaluated using the root of the root mean square error (RMSE) and the correlation coefficient (R). High correlations (greater than 0.94) were made between the measured and predicted values. Finally, the RNA proposal offers a useful alternative for the calculation and prediction of the water quality index in relation to dissolved oxygen (DO), biochemical demand for oxygen (BOD), nitrates, fecal coliforms, potential for hydrogen ions (pH) and turbidity

Model assessment for groundwater quality with elevated arsenic content with application of fuzzy logic

Doktorska disertacija “Model procene kvaliteta podzemne vode sa povećanim sadržajem arsena primenom fazi logike” urađena je kao rezultat potrebe za istraživanjem mogućnosti primene fazi logike u savremenom pristupu procene kvaliteta podzemnih voda. Imajući u vidu da ova tematika nije dovoljno istražena u našem okruženju i da joj nije dat odgovarajući akcenat i težina, osnovni cilj disertacije je da se razrade optimalni modeli za procenu kvaliteta podzemnih voda sa povećanim sadržajem arsena. Disertacija pored teorijske dimenzije prezentuje i primenu evaluiranih fazi modela na primeru eksperimenatlno odabranog lokaliteta grada Zrenjanina. Razvijene modele je moguće transponovati na urbanim i ruralnim područjima uz odgovarajuće iteracije.PhD Thesis “Model assessment for groundwater quality with elevated arsenic content with application of fuzzy logic” was elaborated as a result of the need to explore the possibilities of application of fuzzy logic in the modern approach of assessing the groundwater quality. Because this issue has not been sufficiently explored and it was not given proper emphasis and weight, the main aim of the dissertation is to develop optimal models for assessing the groundwater quality with elevated arsenic content. Dissertation, besides theoretical dimensions, presente and evaluate the implementation of the created models to the experimentaly selected locality of the city of Zrenjanin. The developed models can be transposed to the urban and rural areas with appropriate iteration