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Kernel Methods and Hybrid Evolutionary Algorithms in Energy Forecasting
The development of kernel methods and hybrid evolutionary algorithms (HEAs) to support experts in energy forecasting is of great importance to improving the accuracy of the actions derived from an energy decision maker, and it is crucial that they are theoretically sound. In addition, more accurate or more precise energy demand forecasts are required when decisions are made in a competitive env…
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- ISBN/ISSN
- 978-3-03897-293-8
- Collation
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- Series Title
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- Call Number
- 624 KER
Short-Term Load Forecasting by Artificial Intelligent Technologies
In last few decades, short-term load forecasting (STLF) has been one of the most important research issues for achieving higher efficiency and reliability in power system operation, to facilitate the minimization of its operation cost by providing accurate input to day-ahead scheduling, contingency analysis, load flow analysis, planning, and maintenance of power systems. There are lots of forec…
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- ISBN/ISSN
- 978-3-03897-583-0
- Collation
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- Series Title
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- Call Number
- 003.2 HON s
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