Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)

The demand for water resources in Shaanxi Province increases greatly due to the continuous growth of its population and the rapid development of the social economy. Water demand forecasting is a significant issue in the designing, maintaining and operating of a reliable and economical water supply s...

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Autores principales:	Jun Yang, Yanning Mao, Yuqi Ma, Wei Wu, Yuan Bai
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	accelerated genetic algorithm projection pursuit model regression analysis water demand forecasting Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/7df861c6a1514a048a37d9fba1e76488
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id	oai:doaj.org-article:7df861c6a1514a048a37d9fba1e76488
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spelling	oai:doaj.org-article:7df861c6a1514a048a37d9fba1e764882021-11-06T07:15:45ZIntegrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)1606-97491607-079810.2166/ws.2021.034https://doaj.org/article/7df861c6a1514a048a37d9fba1e764882021-06-01T00:00:00Zhttp://ws.iwaponline.com/content/21/4/1806https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798The demand for water resources in Shaanxi Province increases greatly due to the continuous growth of its population and the rapid development of the social economy. Water demand forecasting is a significant issue in the designing, maintaining and operating of a reliable and economical water supply system. An explicit mathematical method was presented in this study, based on the indicators of industrial output value, such as the gross output value of agriculture, forestry, animal husbandry and fishery. The impact of total retail sales and year trends in the domestic or industrial water demands, can accurately forecast the water demand fluctuations for a municipality. Adopt RAGA-PP optimal selection model through a grouping method of data handling for water demand management to test for the case study Shaanxi, China. Results showed that the prediction effect of multivariate logarithmic model accuracy can reach 99.50%, and it is estimated that the demand for water resources in Shaanxi would exceed 10 billion m3 by 2030. The average relative error of the water consumption from 2015 to 2017 is 3.05% for the model of multiple linear and 0.50% for the model of multivariate logarithm model. Our framework can assist in developing sustainable solutions. HIGHLIGHTS Using the RAGA-PP model to realize the optimal selection of water resources demand indicators can improve model accuracy compared with model solving.; Adopt a curve fitting method and regression analysis method to establish the water demand model and solve it.; Due to the huge consumption of agricultural water, this paper puts forward corresponding agricultural water-saving measures.;Jun YangYanning MaoYuqi MaWei WuYuan BaiIWA Publishingarticleaccelerated genetic algorithmprojection pursuit modelregression analysiswater demand forecastingWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 4, Pp 1806-1816 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	accelerated genetic algorithm projection pursuit model regression analysis water demand forecasting Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	accelerated genetic algorithm projection pursuit model regression analysis water demand forecasting Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Jun Yang Yanning Mao Yuqi Ma Wei Wu Yuan Bai Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
description	The demand for water resources in Shaanxi Province increases greatly due to the continuous growth of its population and the rapid development of the social economy. Water demand forecasting is a significant issue in the designing, maintaining and operating of a reliable and economical water supply system. An explicit mathematical method was presented in this study, based on the indicators of industrial output value, such as the gross output value of agriculture, forestry, animal husbandry and fishery. The impact of total retail sales and year trends in the domestic or industrial water demands, can accurately forecast the water demand fluctuations for a municipality. Adopt RAGA-PP optimal selection model through a grouping method of data handling for water demand management to test for the case study Shaanxi, China. Results showed that the prediction effect of multivariate logarithmic model accuracy can reach 99.50%, and it is estimated that the demand for water resources in Shaanxi would exceed 10 billion m3 by 2030. The average relative error of the water consumption from 2015 to 2017 is 3.05% for the model of multiple linear and 0.50% for the model of multivariate logarithm model. Our framework can assist in developing sustainable solutions. HIGHLIGHTS Using the RAGA-PP model to realize the optimal selection of water resources demand indicators can improve model accuracy compared with model solving.; Adopt a curve fitting method and regression analysis method to establish the water demand model and solve it.; Due to the huge consumption of agricultural water, this paper puts forward corresponding agricultural water-saving measures.;
format	article
author	Jun Yang Yanning Mao Yuqi Ma Wei Wu Yuan Bai
author_facet	Jun Yang Yanning Mao Yuqi Ma Wei Wu Yuan Bai
author_sort	Jun Yang
title	Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
title_short	Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
title_full	Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
title_fullStr	Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
title_full_unstemmed	Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)
title_sort	integrated raga-pp water demand forecast model (case study: shaanxi province, china)
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/7df861c6a1514a048a37d9fba1e76488
work_keys_str_mv	AT junyang integratedragappwaterdemandforecastmodelcasestudyshaanxiprovincechina AT yanningmao integratedragappwaterdemandforecastmodelcasestudyshaanxiprovincechina AT yuqima integratedragappwaterdemandforecastmodelcasestudyshaanxiprovincechina AT weiwu integratedragappwaterdemandforecastmodelcasestudyshaanxiprovincechina AT yuanbai integratedragappwaterdemandforecastmodelcasestudyshaanxiprovincechina
_version_	1718443805032579072

Integrated RAGA-PP water demand forecast model (case study: Shaanxi Province, China)

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