Advanced Hybrid Algorithms in Energy Forecasting
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (31 December 2013) | Viewed by 488
Special Issue Editor
Interests: short-term load forecasting; intelligent forecasting technologies (e.g., neural networks, knowledge–based expert systems, fuzzy inference systems, evolutionary computation, etc.); hybrid forecasting models (e.g., hybridizing traditional models with intelligent technologies, or hybridizing two or more different models to form a novel forecasting model); novel intelligent methodologies (chaos theory; cloud theory; quantum theory)
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The present issue “Advanced Hybrid Algorithms in Energy Forecasting” focuses on energy (including load, energy price, wind speed, and other substitute energy demand) forecasting, which are the prime factors in modern restructured energy market by any novel advanced hybrid algorithm-based techniques to provide significant forecasting accuracy improvements (i.e., proved by statistical test). Advanced hybrid models in this issue is not only concentrated on hybrid evolutionary algorithms or hybrid chaos theory, fuzzy theory, cloud theory with evolutionary algorithms to determine suitable parameters for an existed model, but also on hybridization of two or above existed models, such as neuro-fuzzy model, BPNN-fuzzy model, and so on.
Papers are sought on recent novel ideas by hybridizing intelligent computation algorithms in all fields forecasting in energy sector: genetic algorithm, simulated annealing algorithm, particle swarm optimization, ant colony optimization, immune algorithm, artificial bee colony algorithm, chaotic mapping sequence (including logistic mapping, cat mapping, Tent mapping, and An mapping, etc.), cloud theory, fuzzy theory, artificial neural networks, recurrent mechanism, feed forward mechanism, back-propagation mechanism, seasonal mechanism, etc..
Manuscripts on power transmission design/prediction or IC treatments of economic dispatch scheduling are not targeted in this edition and should be submitted elsewhere.
Dr. Wei-Chiang Hong
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- hybrid algorithms
- energy forecasting model
- hybrid evolutionary algorithms (genetic algorithm, simulated annealing algorithm, particle swarm optimization, ant colony optimization, immune algorithm, artificial bee colony algorithm, fire fly algorithm, harmony search)
- chaotic mapping sequence (logistic mapping, cat mapping, tent mapping, and an mapping)
- cloud theory
- fuzzy theory
- artificial neural networks (recurrent mechanism, feed forward mechanism, back-propagation mechanism)
- seasonal mechanism
- Wavelet transform
