Volume 6 Number 4 (Apr. 2011)
Home > Archive > 2011 > Volume 6 Number 4 (Apr. 2011) >
JSW 2011 Vol.6(4): 716-723 ISSN: 1796-217X
doi: 10.4304/jsw.6.4.716-723

Integration of Grey with Neural Network Model and Its Application in Data Mining

Changjun Zhu1, Qinghua Luan2, Zhenchun Hao3, Qin Ju3

1College of Urban Construction, Hebei University of Engineering, Handan, 056038, China
2College of Water Conservancy and Hydropower, Hebei University of Engineering, Handan, 056038, China
3State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China


Abstract—Because of Boundary types and geologic conditions, which possess random and obscure characteristics, groundwater heads vary with the conditions. The prediction of groundwater level is one of the main work of hydraulic government, which is predicted based on the history data and the relative influence factors. Therefore, prediction precision depends on the accuracy of history data. Data mining has provided a new method for analyzing massive, complex and noisy data. According to the complexity and ambiguity of groundwater system, a new integration of grey with neural network model is built to forecast groundwater heads, which were used to judge whether future groundwater heads were extraordinarily over the history range or not. This method overcomes the disadvantages which the grey method only predict the linear trend. The methods were used to analyze the random characteristics of groundwater heads in anyang city. The results indicate that the method is reliable, and reasonable.

Index Terms—grey degree, groundwater level, neural network, Anyang city

[PDF]

Cite: Changjun Zhu, Qinghua Luan, Zhenchun Hao, Qin Ju, "Integration of Grey with Neural Network Model and Its Application in Data Mining," Journal of Software vol. 6, no. 4, pp. 716-723, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
  • Mar 01, 2024 News!

    Vol 19, No 1 has been published with online version    [Click]

  • Apr 26, 2021 News!

    Vol 14, No 4- Vol 14, No 12 has been indexed by IET-(Inspec)     [Click]

  • Nov 18, 2021 News!

    Papers published in JSW Vol 16, No 1- Vol 16, No 6 have been indexed by DBLP   [Click]

  • Jan 04, 2024 News!

    JSW will adopt Article-by-Article Work Flow

  • Nov 02, 2023 News!

    Vol 18, No 4 has been published with online version   [Click]