Research, Based On The Uml Urban Water Supply Management Information And Decision Support Systems

With the development of computer technology and management science, providing decision support for water supply optimal control and applying DSS in the water service field were the direction of municipal water service management. In point of water supply system optimization, "Decision Support System of Municipal Water Supply System" was studied based on theoretics of system engineering, management science, environment engineering and DSS technology.Firstly, based on static and dynamic modeling mechanism of UML as well as RUP technology, visual and standard models for "Decision Support System of Municipal Water Supply System" was produced. Those models could provide flexible, consistent and legible expression for system analysis, design and realization. Secondly, the system's object, decision-making flow and function structure were analyzed. Thirdly, the system's overall, logical and detailed structures were designed. Finally, with mixed programme technology and on the basis of Database and Knowledge Base, this system was built. It adopted Model Base as decision support means and decision-making disposal as the kernel. This system could analyze a variety of models, algorithms and relevant data for water supply decisions. Besides, it could forecast, simulate, optimize and finally educe optimal schemes for execution. This system was integrated into DSS by interfaces among multi-subassemblies, so that it could realize functions of data query, data maintenance, statistic analysis, water consumption forecast, state simulation of water distribution network and optimization control.From the practical application, it showed that the user interface of this system was friendly, convenient to operate, easy to extend, and it could provide all-around data processing function for water supply enterprises, as well as optimal decisions for administrant institutions. In conclusion, it could shorten optimal decision-making periods, strengthen decision-making analysis abilities, and improve scientific and automated level for administrations.