Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting by Wei-Chiang HongHybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting by Wei-Chiang Hong

Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting

Guest editorWei-Chiang Hong

Paperback | October 18, 2018

Pricing and Purchase Info

$94.60

Earn 473 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

More accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated. Examples include seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. These forecasting models have resulted in an over-reliance on the use of informal judgment and higher expenses when lacking the ability to determine data characteristics and patterns. The hybridization of optimization methods and superior evolutionary algorithms can provide important improvements via good parameter determinations in the optimization process, which is of great assistance to actions taken by energy decision-makers.

This book aimed to attract researchers with an interest in the research areas described above. Specifically, it sought contributions to the development of any hybrid optimization methods (e.g., quadratic programming techniques, chaotic mapping, fuzzy inference theory, quantum computing, etc.) with advanced algorithms (e.g., genetic algorithms, ant colony optimization, particle swarm optimization algorithm, etc.) that have superior capabilities over the traditional optimization approaches to overcome some embedded drawbacks, and the application of these advanced hybrid approaches to significantly improve forecasting accuracy.

Title:Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy ForecastingFormat:PaperbackProduct dimensions:250 pages, 9.61 × 6.69 × 0.68 inShipping dimensions:9.61 × 6.69 × 0.68 inPublished:October 18, 2018Publisher:MDPI AGLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:303897286X

ISBN - 13:9783038972860

Reviews