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J. Agr. Sci. Tech
Water quality assessment provides a scientific basis for water resources development and management. This case study proposes a Factor analysis-Hopfield neural network model (FHNN) based on factor analysis method and Hopfield neural network method. The results showed that the factor analysis (FA) technique was introduced to identify important water quality parameters. Results revealed that biochemical oxygen demand, permanganate index, ammonia nitrogen, nitrogen, Cu, Zn and Pb were the mostfatcat:qsdmfgyy45gy7lpijgfay3zrwe