Petroleum demand forecasting for Taiwan using modified fuzzy-grey algorithms-Reference-Cited by-同舟云学术

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Petroleum demand forecasting for Taiwan using modified fuzzy-grey algorithms

Published:2015-10-09 Issue:1 Volume:33 Page:60-69
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Lu Shin-Li¹,Tsai Chen-Fang¹

Affiliation:

1. Department of Industrial Management and Enterprise Information; Aletheia University; New Taipei City Taiwan

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/exsy.12129/fullpdf

Reference36 articles.

1. Error measures for generalizing about forecasting methods: empirical comparisons;Armstrong;International Journal of Forecasting,1992

2. Electricity consumption forecasting in Italy using linear regression models;Bianco;Energy,2009

3. Forecasting with a nonlinear dynamic model of stock returns and industrial production;Bradley;International Journal of Forecasting,2004

4. Forecast approach using neural network adaptation to support vector regression grey model and generalized auto-regressive conditional heteroscedasticity;Chang;Expert Systems with Applications,2008

5. A variable P value rolling grey forecasting model for Taiwan semiconductor industry production;Chang;Technological Forecasting and Social Change,2005

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2. An MPA-based optimized grey Bernoulli model for China’s petroleum consumption forecasting;Complex & Intelligent Systems;2022-07-01

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4. Improved load forecasting model based on two-stage optimization of gray model with fractional order accumulation and Markov chain;Communications in Statistics - Theory and Methods;2019-10-15

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