Name
Title | ||
|---|---|---|
Development of a web-based decision support system for supporting integrated water resources management in Daegu city, South Korea |
Abstract | ||
|---|---|---|
Demands on fresh water by human beings have been continuously increasing due to population growth, living standard improvement, and economic development. At the same time, many regions are suffering greatly from floods and droughts. Those are the results of ineffective management of water resources due to the associated complexities. In this study, a decision support system (DSS) was developed for supporting integrated water resources management in Daegu city, Republic of Korea. The developed DSS contained four subsystems including database, modelbase, and knowledgebase, as well as general user interface (GUI). It was then connected with the National Water Management Information System (WAMIS). A flow prediction could be conducted through the incorporated HEC-HMS Version 3.0.1. Also, an urban water demand forecasting model was developed using an artificial neural network (ANN) based model. At the same time, a water resources management model based on genetic algorithm (GA) was developed in the DSS, facilitating efficient allocation of water resources among different regions within a city. The result indicated that the developed DSS is very useful to deal with complex water resources management problems and could be further applied to similar cities in South Korea. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.eswa.2012.02.065 | Expert Syst. Appl. |
Keywords | Field | DocType |
urban water demand forecasting,integrated water resources management,developed dss,water resource,water resources management model,fresh water,complex water resources management,daegu city,ineffective management,web-based decision support system,south korea,evolutionary algorithms,decision support system | Water resource management,Management information systems,Environmental resource management,Computer science,Population growth,Integrated water resources management,Artificial intelligence,Web application,Genetic algorithm,Decision support system,User interface,Water resources,Machine learning | Journal |
Volume | Issue | ISSN |
39 | 11 | 0957-4174 |
Citations | PageRank | References |
9 | 0.77 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Zeng | 1 | 9 | 0.77 |
| Yanpeng Cai | 2 | 15 | 3.56 |
| Peng Jia | 3 | 87 | 23.41 |
| Hoogkee Jee | 4 | 9 | 0.77 |