This paper addresses the utilization of predictive modeling and forecasting in the power supply industry. The issues herein were identified a couple of years ago, but the implementation is occurring at this time. The challenge of a forecasting system in power supply is the many "what if" scenarios that different models will need to consider. These "what if" scenarios need to take into consideration:
1. physical assets
2. contract prices
3. economic forecasting
A modeling of this size and complexity could require the utilization of a combination of most of the tools and methodologies in the current data mining and predictive modeling market, plus the development of some new tools.
The latest development in data mining, predictive modeling, marketing analytics, artificial intelligence, analytics, intelligent agents, semiconductors, distributing computing, and network security. SAS, Fair Isaac, Microsoft Analysis Services, SPSS, Cognos, Hyperion, Business Objects, Oracle, KXEN,or R. Healthcare, Pharmaceutical,Retail, CPG, Travel, Financial, Banking, Telecommunications, or Insurance. Unleashing the Power of the Mind©™
Wednesday, September 12, 2007
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Blog Archive
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2007
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September
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- Mobile Business Intelligence - the Next Big Step
- Duke Plots Course Beyond the Smart Grid
- VP, Decision Support Systems
- Market Forecasting and Modeling for the Power Syst...
- Predictive Planning for Supply Chain Management
- F.B.I. Data Mining Reached Beyond Initial Targets
- Frequent Doesn’t Mean Loyal: Using Segmentation Ma...
- Data Mining Analysis and Modeling for Marketing Ba...
- SUPERVISORY [BANK] RISK ASSESSMENT AND EARLY WARNI...
- Data Mining Applications in Higher Education
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September
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About Me
- alberto
- See my resume at: https://docs.google.com/document/d/1-IonTpDtAgZyp3Pz5GqTJ5NjY0PhvCfJsYAfL1rX8KU/edit?hl=en_USid=1gr_s5GAMafHRjwGbDG_sTWpsl3zybGrvu12il5lRaEw
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