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Water Production Forecasting using Adaptive Neuro-Fuzzy Inference System

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Sayyidah Hafidhatul Ilmi, Anik Nur Handayani, Aji Prasetya Wibawa

2018 Proceedings - 2nd East Indonesia Conference on Computer and Information Technology: Internet of Things for Industry, EIConCIT 2018 Conference paper Cited by 1 Quartile

Abstract

Water is essential for human life. Regional Water Supplier piping system may provide clean water for people. The company may need a forecasting system to estimate the water production. This paper implemented an Adaptive Neuro-Fuzzy Inference System (ANFIS) with hybrid learning: Least Square Estimator method and Error Backpropagation methods. The dataset used Generalized Bell membership function and clustered by Fuzzy C-Means (FCM). The selected approach produced 0.364% MAPE error value. © 2018 IEEE.

Affiliations

Department of Electrical Engineering, State University of Malang, Malang, Indonesia

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