Sayyidah Hafidhatul Ilmi, A. N. Handayani, A. Wibawa
{"title":"基于自适应神经模糊推理系统的水量预测","authors":"Sayyidah Hafidhatul Ilmi, A. N. Handayani, A. Wibawa","doi":"10.1109/EIConCIT.2018.8878549","DOIUrl":null,"url":null,"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.","PeriodicalId":424909,"journal":{"name":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Water Production Forecasting using Adaptive Neuro-Fuzzy Inference System\",\"authors\":\"Sayyidah Hafidhatul Ilmi, A. N. Handayani, A. Wibawa\",\"doi\":\"10.1109/EIConCIT.2018.8878549\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":424909,\"journal\":{\"name\":\"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIConCIT.2018.8878549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIConCIT.2018.8878549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Water Production Forecasting using Adaptive Neuro-Fuzzy Inference System
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.
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