کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5064588 1476716 2015 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case
ترجمه فارسی عنوان
پیش بینی مصرف برق کوتاه مدت با استفاده از چارچوب برنامه ریزی ژنتیک مبتنی بر معنایی: پرونده جنوب ایتالیا
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی


- Forecast in energy consumption using a CI system
- System that includes the concept of semantics in the search process
- Results achieved using real data from South Italy regions
- Better results than the ones produced by standard GP and other ML methods

Accurate and robust short-term load forecasting plays a significant role in electric power operations. This paper proposes a variant of genetic programming, improved by incorporating semantic awareness in algorithm, to address a short term load forecasting problem. The objective is to automatically generate models that could effectively and reliably predict energy consumption. The presented results, obtained considering a particularly interesting case of the South Italy area, show that the proposed approach outperforms state of the art methods. Hence, the proposed approach reveals appropriate for the problem of forecasting electricity consumption. This study, besides providing an important contribution to the energy load forecasting, confirms the suitability of genetic programming improved with semantic methods in addressing complex real-life applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Economics - Volume 47, January 2015, Pages 37-41
نویسندگان
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