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Analytics & Modelling Division Activities: A: Quantitative Modelling & Simulation: B: Data Warehousing, OLAP & Data Mining:.

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  1. Analytics & Modelling Division Activities:A: Quantitative Modelling & Simulation: B: Data Warehousing, OLAP & Data Mining:

  2. DETAILED DESCRIPTION:• DSS FOR OPTIMAL IMPORT AND PRODUCTION PLAN FOR MAXIMUM AVAILABILITY OF DAP FERTILIZERUser: Department of Agriculture and Cooperation/Ministry of Agriculture

  3. + Limited Foreign Exchange Availability+ Three Type of Import Options 1. Finished product[i.e.,DAP] 2.Rock Phosphate+Sulphur 3.Phosphoric Acid+Ammonia+ Option 2 and 3 also involves Production Cost+ (Lead) Time Available+ Port Handling Constraints Find out the Import Plan, which gives maximum DAP, which implies maximum utilization of Plants

  4. •COMPUTERIZED RESERVOIR STORAGE AND LEVEL FORECASTING SYSTEM USING ARIMA METHODOLOGYUser: Dhom Dam/Department of Irrigation/Government of Maharashtra+ Daily/Weekly Reservoir Storage Level Monitoring+ Seven days ahead forecast of storage level using Univariate Box Jenkins ARIMA methodology

  5. + MIS Query and Report system+ Graphical display and analyses of storage level+ Implemented in Dhom Dam of satara District, Maharastra+ Developed on UNIX Platform+ With some fine-tuning can be used in other dams

  6. • PDS COMMODITIES DISTRIBUTION AND MOVEMENT PLANNING SYSTEMUser: Department of Food and Civil Supplies/Government of Gujarat+ Fortnightly movement of Wheat and Rice and monthly for Sugar+ Centre allocates the quantity every month [depending on the stock]

  7. + FCI Regional Center, Gujarat identifies the quantity and the godowns from where the state has to lift+ Limited Transport Vehicles+ Limited Time+ Huge Transport Cost involvement+ Software constructs the optimization model; runs; generates the movement plan with minimum cost and time

  8. • FORECASTING AND MONITORING WHOLE SALE PRICE INDICES(WPI)-RATE OF INFLATIONUser: Planning Commission and Ministry of Industry+ Only actual WPI values released by Advisor, Ministry of Industry have been used

  9. + Actual Monthly Data from Apr 1982 to Mar 1993 used+ Unvariate ARIMA Methodology used+ The actual value for monthly price index is obtained after a time lag of two months

  10. + The monthly price index is a simple arithmetic average of the corresponding weekly price indices of the month+ The forecast model equation, along with various error statistics is provided

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