Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China-Reference-Cited by-同舟云学术

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Seasonal forecasting of agricultural commodity price using a hybrid STL and ELM method: Evidence from the vegetable market in China

Published:2018-01 Issue: Volume:275 Page:2831-2844
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Xiong Tao,Li Chongguang,Bao Yukun^ORCID

Funder

Natural Science Foundation of China

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Major Program of National Social Science Foundation of China

Modern Agro-industry Technology Research System

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference49 articles.

1. Canary tomato export prices: comparison and relationships between daily seasonal patterns;Martin-Rodriguez;Span. J. Agric. Res.,2013

2. Time Series Analysis: Forecasting and Control;Box,1976

3. Modeling and forecasting tourism demand for arrivals with stochastic nonstationary seasonality and intervention;Goh;Tourism Manage.,2002

4. Masking of volatility by seasonal adjustment methods;Hayat;Econ. Model.,2013

5. Neural network forecasting for seasonal and trend time series;Zhang;Eur. J. Oper. Res.,2005

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