International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 5, No. 10, 8 Sep. 2013
Cover page and Table of Contents: PDF (size: 329KB)
A New Hybrid Grey Neural Network Based on Grey Verhulst Model and BP Neural Network for Time Series Forecasting
Full Text (PDF, 329KB), PP.114-120
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Author(s)
Deqiang Zhou
1,*
Index Terms
Time Series Prediction, BP Neural Network, Grey Verhulst Model, Grey Neural Network, Grey Verhulst Neural Network
Abstract
The advantages and disadvantages of BP neural network and grey Verhulst model for time series prediction are analyzed respectively, this article proposes a new time series forecasting model for the time series growth in S-type or growth being saturated. From the data fitting's viewpoint, the new model named grey Verhulst neural network is established based on grey Verhulst model and BP neural network. Firstly, the Verhulst model is mapped to a BP neural network, the corresponding relationships between grey Verhulst model parameters and BP network weights is established. Then, the BP neural network is trained by means of BP algorithm, when the BP network convergences, the optimized weights can be extracted, and the optimized grey Verhulst neural network model can be obtained. The experiment results show that the new model is effective with the advantages of high precision, less samples required and simple calculation, which makes full use of the similarities and complementarities between grey system model and BP neural network to settle the disadvantage of applying grey model and neural network separately. It is concluded that grey Verhulst neural network is a feasible and effective modeling method for the time series increasing in the curve with S-type.
Cite This Paper
Deqiang Zhou, "A New Hybrid Grey Neural Network Based on Grey Verhulst Model and BP Neural Network for Time Series Forecasting", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.10, pp.114-120, 2013. DOI:10.5815/ijitcs.2013.10.12
Reference
[1]Kayacan. E, Ulutas. B, & Kaynak. O. Grey system theory-based models in time series prediction[J]. Expert Systems with Applications, 2010, 33(2):1784-1789
[2]Tang Wanmei.Newforecasting model based on grey support vector machine[J].Journal of Systems Engineering, 2006,21(4):410-413(in Chinese).
[3]Jo, T. C. The effect of virtual term generation on the neural based approaches to time series prediction. In Proceedings of the IEEE fourth conference on controland automation, Montreal,Canada, 2003,3: 516-520.
[4]Deng Julong. Contral problems of grey system[J]. Systems & Contral Letters, 1982,1( 5): 288- 294.
[5]Zeng Bo, Liu Sifeng, Xie Naiming. Prediction model of interval grey number based on DGM(1,1)[J].Journal of Systems Engineering and Electronics, 2010,21(4):598-603(in Chinese).
[6]Liu Yucheng.. Anisochronous grey Verhulst GM(1,1) model for certain high building subsidence course[J].The Chinese Journal of Geological Hazard and Control, 2006,17(4):pp.61-63(in Chinese).
[7]Wang Zhengxin, Dang Yaoguo, Liu Sifeng. Unbiased grey Verhulst model and its application[J].Systems Engineering-Theory & Practice. , 2009,29(10):138-144(in Chinese).
[8]F.S. Zhang, F. Liu, W.B. Zhao, “ Application of grey verhulst model in middle and long term load forecasting, ”Power system Technology, vol.27(5) ,pp.37-40, 2003(in Chinese).
[9]F.J.Wang, T.Q. Li, C.Z. Yu. Grey Verhulst Predictive Model of Road Traffic Accidents[J].Journal of Traffic and Engineering, 2006,6(1):122-126 (in Chinese).
[10]D.H. Li.Verhulst model to predicate ground displacement and deformation[I].Coal Science and Technology,2004,32(3): pp.58-59(in Chinese).
[11]Zhang Dahai, Wang Sifang, and Shi KaiQuang.Theoretical Defect of Grey Prediction Formula and Its Improvement[J], Systems Engineering-Theory&Practice, 2002,22(8):140-142(in Chinese).
[12]Zhou Deqiang.Optimization Modeling for GM(1,1) Model Based on BP Neural Network[J]. I. J. Computer Network and Information Security, 2012,1, 24-30.
[13]Zheng Zhaoning, Liu Deshun.Direct Modeling Improved GM (1, 1) Model IGM (1, 1) by Genetic Algorithm[J].Systems Engineering Theory & Practice, 2003,23(5): 99-102(in Chinese).
[14]Xie Naiming, and Liu Sifeng.Discrete GM(1, 1) and mechanism of grey forecasting model[J].Systems Engineering-Theory & Practice, 2005,25(1): 93–99(in Chinese).
[15]Zhou Yatong, Zhang Taiyi, Wang Liejun.On the Relationship between LS-SVM, MSA, and LSA”, International Journal of Computer Science and Network Security[J] 2006,6(11): 01-05.
[16]S. Fan, Y. Fang, W. Li, Y. Ma, and T. Xiao.The combination of grey system and BP neural network.International Conference on Mechatronics and Automation,2007,1267–1271.
[17]C. C. Chiang, M. C. Ho, and J. A. Chen.A hybrid approach of neural networks and grey modeling for adaptive electricity load forecasting[J]. Neural Computing & Applications, 2006, 15(3) 328–338.
[18]F. Wang and H. Xia.Network traffic prediction based on grey neural network integrated model.International Conference on Computer Science and Software Engineering, 2008,915–918.
[19]C. Zhu and Q. Ju.United grey system-neural network model and its application in prediction of ground water level. International Conference on Industrial Mechatronics and Automation, 2009,434–437.
[20]Song Qiang, and Wang Aimin. Simulation and Prediction of Alkalinity in Sintering ProcessBased on Grey Least Squares Support Vector Machine[J].Journal of Iron and Steel Research, International, 2009,16 (5): 01-06(in Chinese).
[21]Yuan Jingling,Zhong Luo,Li Xiao-yan.The Research and Development of Grey Neural Network[J].Journal of Wuhan University of Technilogy, 2009,31(3): 91-93(in Chinese).
[22]Zhong Luo, Bai Zhengang, Xia Hongxia.. Optimization and Application of Neural Network Modeling for Gray Problem[J].Computer Engineering and Applications, 2001,37(9):33-35(in Chinese).
[23]Guo Zijian, Song Xiangqun, Ye Jian. A Verhulst Model on Time Series Error Corrected for Port Throughput Forecasting[J].Journal of the Eastern Asia Society for Transportation Studies, 2005, 6, 881 – 891.
[24]Xiao Yi, Xiao Jin, Wang Shouyang, A Hybrid Forecasting Model for Non-Stationary Time Series:An Application to Container Throughput Prediction[J], International Journal of Knowledge and Systems Science, 2012,3(2): 67-82.
[25]Deng Julong. The Basis of Grey Theory[M]. Wuhan: Press of Huazhong University of Science & Technology, 2002(in Chinese).
[26]C. Lewis. Industrial and Business Forecasting Methods[M]. Butterworth Scientific, London, 1982.