دورية أكاديمية

Power load forecasting algorithm based on nonlinear inertial factor change pattern particle swarm optimization algorithm

التفاصيل البيبلوغرافية
العنوان: Power load forecasting algorithm based on nonlinear inertial factor change pattern particle swarm optimization algorithm
المؤلفون: Liang Jin, Yongzhi Wang, Xiaodong Bao
المصدر: MATEC Web of Conferences, Vol 173, p 02016 (2018)
بيانات النشر: EDP Sciences, 2018.
سنة النشر: 2018
المجموعة: LCC:Engineering (General). Civil engineering (General)
مصطلحات موضوعية: Engineering (General). Civil engineering (General), TA1-2040
الوصف: The common method of power load forecasting is the least squares support vector machine, but this method is very dependent on the selection of parameters. Particle swarm optimization algorithm is an algorithm suitable for optimizing the selection of support vector parameters, but it is easy to fall into the local optimum. In this paper, we propose a new particle swarm optimization algorithm, it uses non-linear inertial factor change that is used to optimize the algorithm least squares support vector machine to avoid falling into the local optimum. It aims to make the prediction accuracy of the algorithm reach the highest. The experimental results show this method is correct and effective.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 2261-236X
Relation: https://doaj.org/toc/2261-236X
DOI: 10.1051/matecconf/201817302016
URL الوصول: https://doaj.org/article/3fb30c624c0c4cf1ab91708d31bcd264
رقم الأكسشن: edsdoj.3fb30c624c0c4cf1ab91708d31bcd264
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2261236X
DOI:10.1051/matecconf/201817302016