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Particle swarm grammatical evolution for energy demand estimation

التفاصيل البيبلوغرافية
العنوان: Particle swarm grammatical evolution for energy demand estimation
المؤلفون: David Martínez‐Rodríguez, J. Manuel Colmenar, J. Ignacio Hidalgo, Rafael‐J. Villanueva Micó, Sancho Salcedo‐Sanz
المصدر: Energy Science & Engineering, Vol 8, Iss 4, Pp 1068-1079 (2020)
بيانات النشر: Wiley, 2020.
سنة النشر: 2020
المجموعة: LCC:Technology
LCC:Science
مصطلحات موضوعية: energy prediction models, grammatical swarm evolution, macroeconomic variables, total energy demand, Technology, Science
الوصف: Abstract Grammatical Swarm is a search and optimization algorithm that belongs to the more general Grammatical Evolution family, which works with a set of solutions called individuals or particles. It uses the Particle Swarm Optimization algorithm as the search engine in the evolution of solutions. In this paper, we present a Grammatical Swarm algorithm for total energy demand estimation in a country from macroeconomic variables. Each particle in the Grammatical Swarm encodes a different model for energy demand estimation, which will be decoded by a predefined grammar. The parameters of the model are also optimized by the proposed algorithm, in such a way that the model is adjusted to a training set of real energy demand data, selecting the more appropriate variables to appear in the model. We analyze the performance of the Grammatical Swarm evolution in two real problems of one‐year ahead energy demand estimation in Spain and France. The proposal is compared with previous approaches with competitive results.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2050-0505
Relation: https://doaj.org/toc/2050-0505
DOI: 10.1002/ese3.568
URL الوصول: https://doaj.org/article/2294219b681e41c89e98089898d72105
رقم الانضمام: edsdoj.2294219b681e41c89e98089898d72105
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20500505
DOI:10.1002/ese3.568