کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10321712 660749 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Regularized multivariable grey model for stable grey coefficients estimation
ترجمه فارسی عنوان
مدل خاکستری چند متغیره مرتب برای ارزیابی ضرایب خاکستری پایدار
کلمات کلیدی
مدل خاکستری چند متغیره، مشکل منفی، منظم سازی، شاخص های صنعتی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Recently, the convolution integral-based multivariable grey model (GMC(1, N)) has attracted considerable interest due to its significant performance in time series forecasting. However, this promising technique may occasionally confront ill-posed problem, which is a plague ignored by most researchers. In this paper, a regularized GMC(1, N) framework (R-GMC(1, N)) is proposed to estimate the grey coefficients in case there exists potential ill-posed problem. More specifically, we adopt two state-of-the-art regularization methods, i.e. the Tikhonov regularization (TR) and truncated singular value decomposition (TSVD), together with two regularization parameters detection methods, i.e. L-curve (LC) and generalized cross-validation (GCV), to identify the stable solutions. Numerical simulations on industrial indicators of China demonstrate that our methods yield more accurate forecast results than the existing GMC(1, N).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 42, Issue 4, March 2015, Pages 1806-1815
نویسندگان
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