Forecasting Value of Pollutant Index in Surabaya River Using Fuzzy Radial Basis Function Neural Network

Nisa Ayunda, Mohammad Isa Irawan, Nieke Karnaningroem

Abstract


Water resources quality for people in around Surabaya River is an important thing that can be laid aside so it need a management and monitoring system for water quality of Surabaya River. One form of monitoring system for Surabaya River water quality is trend analysis of the system, so it can be used to identify the water system and forecast the next condition. Radial basis function neural network model can be used to analyze the tendency of the water system is based on time series data of the pollutant index value. Taking into account the possibility of parallax error in the measurement, the limited data, and different data characteristics, application of fuzzy theory is imposed on the model. Application of fuzzy theory is also based on its ability for measure the uncertainty by the lower and upper bound. Fuzzy radial basis function neural network model formed expected to give results close to the actual value of forecasting on the testing step of simulation models. Forecasting results obtained pollution index values can also be used as a reference in the management and monitoring system of Surabaya River.

 


Keywords


Fuzzy radial basis function, Pollutant index, Surabaya river

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References


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