The main objectives of present study are to evaluate the trace elements pollution in the sediment of the Tigris River and drainage canals in Wasit Governorate, Iraq. Assessment of trace elements pollutants were conducted for 18 sediment samples collected in March 2017. Trace elements were analyzed in sediment Tigris River samples in Wasit Governorate. This metal pollution was evaluated using geo-accumulation (I-geo) index, Contamination Factor (CF) and Pollution Load Index (PLI). According to these statistical indices, the sediments collected from Tigris River in the study area are highly polluted with Titanium (71.9 ppm), Nickel (226.6 ppm) Chromium (425.2 ppm), Cadmium (2ppm) and Molybdenum (15.8 ppm) while the sediments were moderately polluted with Cobalt (25.1 ppm), Strontium (839.3 ppm), Copper (56.2), Manganese (106.1ppm), Vanadium (135 ppm), Niobium (9.79 ppm). However, the sediments of the Tigris River is not polluted by Lead, Barium, Gallium, Rubidium and, Zinc. Metals concentration levels in the sediments of the drainage canals that discharged into the Tigris River showed higher concentrations than the Tigris sediments in Ta, V, Ni, Cu, Ga, Br, Sr and Mo.
The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
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