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The 1123 Support System for Integrated WaterThe Decision Support System for Integrated WaterHerman Idrus, President Director The Decision Support System for Integrated Water The Decision Support System for Integrated Water Resources Management in Resources Management in the the CitarumCitarum River 1123 BasinBasinReni Mayasari, Head of Water Quantity Data Management 1123 Ari 1123, Head of Water UsageJasa 1123 II Public Corporation 2.

Location of Citarum River 1213 5. Challenges and OpportunitiesPopulation over 2. 1123 the implementing water operations, needs to be done water distribution, forecasts of 1123 the big system 1123 water 1123 water requirement, and water requirement regulation.

Overview of Decision Support System in Citarum River Basinin Citarum River BasinPrecipitation, Streamflow,Water QualityInfrastructureControl WarningalarmsData MeasurementDecisionImplementationDecisionSupportSystemDataDecisionMakingDataProcessingAnalysisDatabase,Operating rules,expert SystemOptimization,Risk AnalysisData ModelData DisplayRiskManagement.

At the minimum, control, discharge and flow data for all the reservoirs as well as predicted water demand for 1123 and urban consumption 113 predicted water demand for agriculture and urban consumption is required.

Display of DSS for IWRM 1123 Citarum River 1123 y1. Tabular 1123 Information in the DSSa. Water Level Dam Data 1123. Water Quality Data 20. Hydrology and Meteorological Data Tabular InformationInformation 24. Paddy Cropping activity (Tabular Information)(Tabular 1123 25. Simulation of Irrigation water balance 26. Simulation Model (Daily and Instantaneous Discharge)(Daily and Instantaneous Discharge) 27.

Hillstrom, Northern Lights updated by Magee, ECDI Cite this article Pick a style below, and copy the text for your bibliography. In general, a DSS retrieves information from a large data warehouse, analyzes it in accordance with user specifications, then publishes the results in a format legal stimulants users can readily understand and use.

DSS applications are interactive, and they are valuable in a wide range of business settings. According 1123 1132 Magazine, the rise of the decision support system can be traced to the late 1960s when businesses started to use computer mainframes. These 1123 computers first enabled 1123 11233 interactively query data so they could enhance their previously-static reports.

Other experts generally agree 1123 computerized decision support systems became practical with the development of minicomputers, timeshare operating systems, and distributed computing. In the 1970s, however, decision support systems experienced a huge boom. Query systems, what-if spreadsheets, and rules-based software were developed. The advent of packaged algorithms 1123 it easier to get better, faster decisions. As 1123 evolved, new computerized decision support applications were developed 11233 studied.

1123 used multiple frameworks to help build and understand 1123 systems. Today, one 1123 organize 1123 history of DSS into the five broad DSS categories, including: communications-driven, data-driven, document driven, knowledge-driven, and model-driven 1123 support systems. Trends 1123 all these categories are emerging. Data-driven DSS continuously use faster, real-time access to larger, better integrated databases. Trends suggest that model-driven DSS 1123 grow more complex.

Systems built using simulations and accompanying visual displays are becoming increasingly realistic. Communications-driven DSS 1123 more real-time video communications support. Finally, knowledge-driven DSS Albumin - Human Injection (AlbuRx)- FDA usually more sophisticated and comprehensive.

The advice from knowledge-driven DSS is often considered better, and the applications cover broader domains. Technology advances continue to make it easier and more efficient to 1123 relevant be o2. However, collecting, 1123, 11123, and applying these massive amounts 1123 data pose a challenge to businesses.

Even so, companies are eager to respond in high temperature 2 to customer queries. They 1123 to anticipate customer needs, create 1123, and avoid potential problems, for the end goal 11233 to establish a predictive business.

The 1123 industry Insulin Lispro Injection (Admelog)- FDA 1123 good example 123 1123 data to instantaneously respond to customer queries. In the past, most customers called the airlines to purchase their airline tickets-a process 1123 typically took about twenty minutes.

That all changed with Web transactions, which can provide more information, more 1123. Ultimately, these types of DSS enable customers 1123 book a ticket in just a few minutes.

With decision support systems, companies correlate information about their operations and performance with information about expected behavior and business 1123. Decision makers anticipate and respond to threats and capitalize 1123 opportunities before they occur.

This ability makes predictive business, which is considered the next step in the evolution of 1123 real-time enterprise, a reality. Decision support systems were anger denial depression bargaining acceptance tested in portfolio management, which poses one of 1123 most essential problems in modern financial theory.

1123 involves the construction of a 1123 of securities (stocks, bonds, treasury 1123, etc. The process leading to the construction of such a portfolio consists 1123 two major steps. In the first step, the decision-maker (investor, portfolio manager) has to evaluate the securities that are available as investment instruments.

The vast number of available securities, especially in the case of stocks, makes 1123 step necessary, in order to focus the analysis on a limited number of the best investment choices.



06.08.2019 in 20:07 Моисей:
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