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Application of a Novel Approach of Artificial Intelligence in Forecasting Global Solar Radiation and Gas Consumption in Iran

Saeidi Ramyani, Sara | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 44081 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Shavandi, Hassan
  7. Abstract:
  8. Energy is of the essential elements to improve every nation’s economy and society, which is influenced by a variety of parameters. Thus many empirical methods have been represented to assess the said parameters using other parameters by which they are affected. In this research, Linear Genetic Programming method (LGP) has been used for assessment, which has been applied to project the global shining of the sun in two Iranian metropolises (Tehran and Kerman), and also natural gas utilization in both industrial and domestic sectors. In this research, authentic data from the empirical results existing in technical documents has been used to develop the models. Most prevalent effective parameters used in the past researches have been applied as the projecting variables. In order to study the performance of the research outcomes, the models obtained from assessing both global shining of the sun and natural gas utilization have been tested on the validation data. The results indicate that the LGP method assesses the target variable with a better performance compared to linear models prevalent in technical documents. Subsequently, by sensitivity analysis, the relative significance of the input variables in the obtained models has been calculated in order to project the models’ output
  9. Keywords:
  10. Solar Radiation ; Forecasting ; Gas Consumption ; Linear Genetic Programming

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