Rahmatnia,Mehran

Water Quality Zoning of Rivers by the Combination of Fuzzy Clustering and Principal Component Analysis (PCA) A Case Study: Zayandeh-rud

For water quality management, knowledge of the facts and use of models and tools that the tra arent results, reliable and applicable to lose, is imperative and inevitable. One of these management tools is water quality zoning models.

River water quality zoning, is considered the first and may the most important step in the management of river water quality. Because it makes the analyst to see how the process of pollution changes over time, place and circumstances clearly. Recognition of the quality of surface water for drinking, industry and agriculture seems inevitable. Identification of contaminated sites and contaminated area make optimum and appropriate use of water in various uses. Along with technology development, more information, with conditions more easily and in shorter time is given to humans. In the case of surface water, must process the relevant information, and present the summarized results for different applications to the experts.

In this regard, an important issue that there is a reasonable criterion to determine and correct for the contamination. In determining this criterion, the quality parameters of water quality due to pollution and its control objectives can participate. Taking together all these parameters for water quality analysis can be a difficult and complex river and eventually require the analyst to use the tools and models that are more close to reality that they are necessary.

The "fuzzy inter-ideograph; TEXT-ALIGN: justify; LINE-HEIGHT: normal; MARGIN: auto auto 0pt; mso-add-space: auto" >This method approach to this issue can be investigated from two useful aspects. The first aspect is the abundance and variety of data on river pollution problems which have always been misleading for management decisions. To fix this, simple methods and techniques have been used for that also turn out to have problems. Mathematical methods of inter-ideograph; TEXT-ALIGN: justify; LINE-HEIGHT: normal; MARGIN: auto auto 0pt; mso-add-space: auto" >The "Principal Component Analysis" method used to reduce the number of components in order to summarize and consolidate to fewer indicators of the information. In the main component method, several indicators taken together and then the most striking characteristic which shows difference represent is that in principle are identified as components and then the solidarity with these indicators will be destroyed.

The thesis has tried to combine the two methods using fuzzy inter-ideograph; TEXT-ALIGN: justify; LINE-HEIGHT: normal; MARGIN: auto auto 0pt; mso-add-space: auto" >

Keywords: water quality zoning, fuzzy 0in 0in 10pt" >