A local field correlated and Monte Carlo based shallow neural network model for nonlinear time series prediction

Zhou, Qingguo and Chen, Huaming and Zhao, Hong and Zhang, Gaofeng and Yong, Jianming and Shen, Jun (2016) A local field correlated and Monte Carlo based shallow neural network model for nonlinear time series prediction. EAI Endorsed Transactions on Scalable Information Systems, 16 (8). pp. 1-7. ISSN 2032-9407

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Abstract

Water resource problems currently are much more important in proper planning especially for arid regions, such as Gansu in China. For agricultural and industrial activities, prediction of groundwater status is critical. As a main branch of neural network, shallow artificial neural network models have been deployed in prediction areas such as groundwater and rainfall since late 1980s. In this paper, artificial neural network (ANN) model within a newly proposed algorithm has been developed for groundwater status forecasting. Having considered previous algorithms for ANN model in time series forecast, this new Monte Carlo based algorithm demonstrated a good result. The experiments of this ANN model in predicting groundwater status were conducted on the Heihe River area dataset, which was curated on the collected data. When compared with its original physical based model, this ANN model was able to achieve a more stable and accurate result. A comparison and an analysis of this ANN model were also presented in this paper.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright © 2016 Vimalachandran et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
Faculty / Department / School: Current - Faculty of Business, Education, Law and Arts - School of Management and Enterprise
Date Deposited: 13 Sep 2016 00:38
Last Modified: 08 Mar 2018 01:37
Uncontrolled Keywords: groundwater status forecasting; planning; arid regions
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080612 Interorganisational Information Systems and Web Services
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.4108/eai.9-8-2016.151634
URI: http://eprints.usq.edu.au/id/eprint/29602

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