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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The results show that the Markov Chain residual modification model achieves reliable and precise results
📌 3 Key Takeaways
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Objective & Hypothesis:Grey theory deals with systems that are characterized by poor information or for which information is lacking.
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Key Findings & Data:This study presents an improved grey GM (1, 1) model, using a technique that combines residual modification with Markov Chain model.
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Conclusion & Impact:The results show that the Markov Chain residual modification model achieves reliable and precise results
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Grey Forecasting Model · Markov Chain · Energy System
Abstract
Grey theory deals with systems that are characterized by poor information or for which information is lacking. This study presents an improved grey GM (1, 1) model, using a technique that combines residual modification with Markov Chain model. We use energy consumption and supply of Iran to test the accuracy of proposed model. The results show that the Markov Chain residual modification model achieves reliable and precise results
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Cite This Article
Mostafaei, H., Kordnoori, S. (2012). Hybrid Grey Forecasting Model for Iran’s Energy Consumption and Supply. International Journal of Energy Economics and Policy, Cilt: 2 Sayı: 3, 97–102. https://ajindex.com/articles/1653214