Titlebook: Smart Water Resource Management; A Practical Introduc Ana Cristina Faria Ribeiro,A. K. Haghi Book 2025 The Editor(s) (if applicable) and Th

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書(shū)目名稱(chēng)Smart Water Resource Management影響因子(影響力)




書(shū)目名稱(chēng)Smart Water Resource Management影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Smart Water Resource Management網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Smart Water Resource Management網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Smart Water Resource Management被引頻次




書(shū)目名稱(chēng)Smart Water Resource Management被引頻次學(xué)科排名




書(shū)目名稱(chēng)Smart Water Resource Management年度引用




書(shū)目名稱(chēng)Smart Water Resource Management年度引用學(xué)科排名




書(shū)目名稱(chēng)Smart Water Resource Management讀者反饋




書(shū)目名稱(chēng)Smart Water Resource Management讀者反饋學(xué)科排名

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Smart Water Resource Management978-3-031-60799-8Series ISSN 2381-1412 Series E-ISSN 2381-1439

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Synthesis Lectures on Emerging Engineering Technologieshttp://image.papertrans.cn/s/image/869066.jpg

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Apparent Water Loss Control Based on the Geographic Information Systems (GIS),d on the Geographic Information Systems (GIS). The aim of the current work was to investigate the amount of apparent water loss in the water distribution network. In this regard, the total amount of apparent losses was calculated for the number of 200 consumers in an isolated area. The results of th

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Smart Management of Water Loss at the District Metered Areas (DMA),er in DMA showed that physical losses are under the direct influence of fluid working pressure changes. In the regression analysis, the fluid working pressure in the water distribution network as a dependent variable of changes in the outflow water of the reservoir (incoming water flow to the DMA) h

Anticonvulsants

Computational Modeling and Regression Analysis for Water Consumption Management,ed water consumption characteristics. In this method, per capita consumption is calculated. Per capita consumption is multiplied by the projected population. The predicted amount of water is compared with the capacity of the network. In this way, the surplus or shortage of predicted water is determi

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Advanced Technologies and Forecasting Models for Water Demand,hree groups: short-term, medium-term, and long-term forecasting. Usually, forecasts of one to two years, short-term forecasts, between one to ten years, and mid-term and longer periods are classified as long-term forecasts. The water demand forecast investigated consumption (m./year) in the isolatio