Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization

Author:

Huang Daizheng,Wu Zhihui

Funder

the project of Basic Ability Promotion for Young Teachers of the Guangxi Education Department

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference43 articles.

1. Forecasting the number of outpatient visits using a new fuzzy time series based on weighted-transitional matrix;CH Chenga;EXPERT SYST APPL,2008

2. An improved sales forecasting approach by the integration of genetic fuzzy systems and data clustering: Case study of printed circuit board;E Hadavandi;EXPERT SYST APPL,2011

3. Diarrhoea outpatient visits prediction based on time series decomposition and multi-local predictor fusion;Y Wang;KNOWL-BASED SYST,2015

4. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis;N E Huang;Proceedings: Mathematical, Physical and Engineering Sciences,1998

5. Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method;S Wang;RENEW ENERG,2016

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