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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书目名称Smart Water Resource Management影响因子(影响力)




书目名称Smart Water Resource Management影响因子(影响力)学科排名




书目名称Smart Water Resource Management网络公开度




书目名称Smart Water Resource Management网络公开度学科排名




书目名称Smart Water Resource Management被引频次




书目名称Smart Water Resource Management被引频次学科排名




书目名称Smart Water Resource Management年度引用




书目名称Smart Water Resource Management年度引用学科排名




书目名称Smart Water Resource Management读者反馈




书目名称Smart Water Resource Management读者反馈学科排名

instate

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

Mundane

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

不理会

intolerance

Pathogen

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

蔑视

调整校对

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

袋鼠

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