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Application of Heuristic Rules and Genetic Algorithm in ARMA Model Estimation for Time Series Prediction | ||
| Journal of Information Technology Management | ||
| مقاله 1، دوره 8، شماره 1، تیر 2016، صفحه 1-26 اصل مقاله (1.14 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2016.55761 | ||
| نویسندگان | ||
| Mohammadreza Asghari Oskoei1؛ Mohammad Ghasemmzade* 2 | ||
| 1Assistant Prof./ Allameh Tabataba'i University | ||
| 2student/Allameh Tabataba'i University | ||
| چکیده | ||
| The first step of forecasting time series is to build an appropriate model. Determining orders and estimation of ARMA model parameters is a challenging field in traditional statistical and intelligent methods. In this paper, genetic algorithm is used for parameter estimation and heuristic rules are used to determine orders of ARMA model. Heuristic rules are extracted according to time series properties. The data are selected using sliding time window. Model identification is carried out by using Bayesian information criterion (BIC). The mean squares error and the mean absolute percentage error are used to evaluate the results of prediction. The proposed method was applied to eight time series in different types, and the results were compared with results of statistical methods. The achieved result shows equivalent or superior performance for the proposed method in comparison with the classic method. | ||
| کلیدواژه‌ها | ||
| ARMA model estimation؛ Genetic Algorithm؛ heuristic rules؛ time series prediction | ||
| عنوان مقاله [English] | ||
| کاربرد قواعد کشفی و الگوریتم ژنتیک در ساخت مدل ARMA برای پیش بینی سری زمانی | ||
| نویسندگان [English] | ||
| محمد رضا اصغری اسکویی1؛ محمد قاسم زاده2 | ||
| 1استادیار رایانه، دانشکدۀ علوم ریاضی و رایانه، دانشگاه علامه طباطبائی، تهران، ایران | ||
| 2دانشجوی کارشناسی ارشد علوم رایانه ـ گرایش سیستمهای هوشمند، دانشکدۀ علوم ریاضی و رایانه، دانشگاه علامه طباطبائی، تهران، ایران | ||
| چکیده [English] | ||
| برای پیشبینی سری زمانی ابتدا باید مدل مناسبی از آن ساخته شود. تعیین ابعاد و تخمین پارامترهای مناسب برای مدل ARMA سری زمانی، چالشی است که علاوه بر روشهای متداول آماری، از طریق محاسبات هوشمند نیز به آن توجه شده است. در این مقاله استفاده از الگوریتم ژنتیک برای تخمین پارامترهای مدل ARMA و قواعد کشفی برای تعیین ابعاد مدل ارائه میشود. قواعد کشفی بر‌اساس ویژگیهای سری زمانی استخراج میشوند. دادهها به‌روش پنجرۀ لغزان در پیشبینی بهکار میروند. مدل بر اساس معیار اطلاعاتی بیزین و پیشبینی بر اساس دو معیار مجذور متوسط مربعات خطا و متوسط قدر مطلق درصد خطا ارزیابی میشود. روش ارائهشده روی هشت سری زمانی با ویژگیهای مختلف بهکار رفته و نتایج آن با نتایج روش آماری مقایسه شده است. نتایج نشان میدهد در تمام موارد، روش ارائهشده همسان یا بهتر از روش کلاسیک عمل میکند. | ||
| کلیدواژه‌ها [English] | ||
| الگوریتم ژنتیک, پنجرۀ لغزان, پیشبینی سری زمانی, تخمین مدل ARMA, قواعد کشفی | ||
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