Performance Evaluation Model of Engineering Project Management Based on Improved Wavelet Neural Network

DOI: 10.4236/jssm.2009.21002   PDF   HTML     7,194 Downloads   12,640 Views   Citations

Abstract

The scientific and reasonable performance evaluation is advantageous to promote the comprehensive management level of engineering projects. Benefited from constrictive and fluctuant of wavelet transform and self-study, self-adjustment and nonlinear mapping functions of wavelet neural network (WNN), and based on the existing assessment method and the index system, the performance evaluation model of engineering project management is established. One company is taken as the study object for this model. Compared with the conventional method, the influence of human factor is eliminated, thus the objectivity of the measure results is increased. A satisfactory result is concluded, thus a new ap-proach is presented for engineering project management performance evaluation.

Share and Cite:

Q. Zhang and Q. Fu, "Performance Evaluation Model of Engineering Project Management Based on Improved Wavelet Neural Network," Journal of Service Science and Management, Vol. 2 No. 1, 2009, pp. 10-14. doi: 10.4236/jssm.2009.21002.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] L. X. Zhang, “Fuzzy comprehensive evaluation of the expressway project management performance evalua-tion,” Road traffic technology (applications) 5, pp. 169-171, 2007.
[2] S. H. Cai, M. Y. Zhou, and Z. C. Ye, “Fuzzy integrative evaluation method of management performance of engi-neering project,” Journal of YangZhou university (natural science), 5, pp. 57-60, 2002.
[3] V. Ireland, “The role of management actions in the cost, time and quality performance of high-rise commer cial building projects,” Construction Management and Economics, 3, pp. 59-87, 1985.
[4] T. Brian and H. Szu, “Adaptive wavelet classification of acoustic backscatter and imagery,” Optical Engineering, 7, pp. 2192-2202, 1994.
[5] Q. H. Zhang and A. Benveniste, “Wavelet networks,” IEEE Transactions on Neural Networds, 6, 889-898, 1992.
[6] X. Y. Zhao., Q. Fu, and Z. X. Xing, “Application of pro-jection pursuit grade evaluation model in comprehensive evaluation of changes in soil quality,” Acta Pedologica Sinica. 1, pp. 164-168, 2007.

  
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