Water Hardness Prediction using Fuzzy Subtractive Clustering and GRNN
Sandeep Kumar Sunori, Amit Mittal, Farha Khan, Mehul Manu, Pawan Agarwal, Pradeep Kumar Juneja · 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) · 2022
Softcomputing methods e. g. Fuzzy Logic, ANN, GA etc. have proven to be very fast and effective techniques for solving the classification and regression problems. They can be very well applied to both linear and non-linear data. The results can be further improved by combining these techniques to build a hybrid model. The present article addresses the anticipation of hardness of water. The prediction models based on the fuzzy subtractive clustering and GRNN (General Regression Neural Network) techniques have been developed in MATLAB using the available raw data pertaining to the water hardness of lake. A comparative analysis is also presented of the developed models.