A new fuzzy weighted multivariate regression to predict water quality index at perak rivers

Fuzzy weighted multivariate regression analysis is proposing to assess the water pollution based on water quality index (WQI). In this research the data used to test the performance of the proposed approach were collected from several locations of Perak River at Perak State, Malaysia. The water quality index was monitored during the year 2013-2017. The water quality index (WQI) are express water quality by integrating measurements of six (6) selected water quality parameters is pH, chemical oxygen demand, ammoniacal nitrogen, dissolved oxygen, suspended solid and biochemical oxygen demand (BOD). The index was developed for the purpose of providing a simple, concise and valid method for expressing the significance of regularly generated laboratory data and water quality for compliance with the Standards adopted for 6 designated classes of beneficial uses. The WQI provides a basis to evaluate effectiveness of water quality improvement and assist in establishing priorities for management purpose even though it is not meant specifically as an absolute measure of the degree of pollutant or the actual water quality. A fuzzy Logic approach has shown to be practical, simple and useful tool to assess the water pollution levels. The proposed in this study is we create new model of WQI according to the standard prepared by Department of Environmental (DOE), Malaysia-involving all six parameters. The main difference is the model that we are proposing. The expected results are: (a) Relationships between all six parameters with WQI (b) New Fuzzy based on multivariate regression analysis to be developed that will outperform some existing at Perak River or other river in Malaysia and Indonesia. The model is line with the National Water Quality Standards for Malaysia. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020.