کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
559289 1451729 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
From nature to maths: Improving forecasting performance in subspace-based methods using genetics Colonial Theory
ترجمه فارسی عنوان
از طبیعت به ریاضی: بهبود عملکرد پیش بینی در روش های مبتنی بر زیر فضای با استفاده از ژنتیک نظریه استعمار
کلمات کلیدی
تئوری استعماری، پیش بینی، طبیعت الگوریتم الهام گرفته، روش های زیر فضای
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی

Many scientific fields consider accurate and reliable forecasting methods as important decision-making tools in the modern age amidst increasing volatility and uncertainty. As such there exists an opportune demand for theoretical developments which can result in more accurate forecasts. Inspired by Colonial Theory, this paper seeks to bring about considerable improvements to the field of time series analysis and forecasting by identifying certain core characteristics of Colonial Theory which are subsequently exploited in introducing a novel approach for the grouping step of subspace based methods. The proposed algorithm shows promising results in terms of improved performances in noise filtering and forecasting of time series. The reliability and validity of the proposed algorithm is evaluated and compared with popular forecasting models with the results being thoroughly evaluated for statistical significance and thereby adding more confidence and value to the findings of this research.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 51, April 2016, Pages 101–109
نویسندگان
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