# مدل بندی سری های زمانی ناپارامتری بر اساس داده های فازی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه آمار دانشگاه پیام نور، صندوق پستی ۱۹۳۹۵ -۴۶۹۷ تهران، ایران

2 گروه آمار، دانشکده علوم ریاضی،دانشگاه بیرجند، خراسان جنوبی، ایران

چکیده

در این مقاله، یک مدل سری زمانی ناپارامتری بر اساس مشاهدات فازی ارائه شده و با استفاده از تعمیم روش
نادارایا-واتسون در محیط فازی، برآورد مقادیرفازی پیش بینی شده بدست می آید. در این راستا الگوریتمی جهت دستیابی به
مرتبه اتورگرسیو و پهنای باند بهینه بیان شده و سپس معیارهایی برای بررسی ارزیابی پیش بینی معرفی می گردد. در ادامه
با استفاده از داده های واقعی کارایی مدل پیشنهادی مورد بررسی و تحلیل قرار می گیرد. همچنین تأثیر مدل سری زمانی
پیشنهادی در پیش بینی با سایر مدل های سری زمانی با داده های فازی مورد مقایسه قرار می گیرد

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

### Nonparametric Time Series Modeling based on Fuzzy Data

نویسندگان [English]

• Faezeh Torkian 1
• Gholamreza Hesamian 1
1 Department of Statistics, Payame Noor University, Tehran 19395-4697, Iran
2 Department of Statistics, University of Birjand, Birjand 615-97175, Iran.
چکیده [English]

In this paper, a nonparametric time series model based on fuzzy observations is presented.
Fuzzy prediction values are estimated using the generalization of the Nadaraya-Watson method in a fuzzy environment. An algorithm for achieving autoregressive order and optimal bandwidth is stated and then criteria are introduced to evaluate the prediction values. In the following, the performance of the proposed model is examined and analyzed using real data. The effectiveness of the proposed model is also compared with the other time series models with fuzzy data.

کلیدواژه‌ها [English]

• Fuzzy nonparametric time series
• kernel method
• optimal bandwidth
• autoregressive order

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### سابقه مقاله

• تاریخ دریافت: 14 فروردین 1400
• تاریخ بازنگری: 05 مرداد 1400
• تاریخ پذیرش: 12 مرداد 1400