Construction Quality Residential Project Based on Artificial Neural Network - Open Access Library Journal

OALibJ > Vol.6 No.8, August 2019

Construction Quality Residential Project Based on Artificial Neural Network ()

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DOI: 10.4236/oalib.1105681 247 Downloads 653 Views

Author(s)

Yue Yue¹, Jiaye Wu^2*, Shuyang Liu¹, Yingqian Zhang³

Affiliation(s)

¹School of Management of Sichuan University of Science & Engineering, Zigong, China.
²Sichuan Shengtuo Testing Technology Co., LTD., Zigong, China.
³School of Civil Engineering of Sichuan University of Science & Engineering, Zigong, China.

ABSTRACT

Engineering quality evaluation is an important part of engineering quality management. However, China has not yet formed a systematic engineering quality evaluation system. Aiming at such problems, a comprehensive evalua-tion method based on artificial neural network for residential project construc-tion quality is proposed. Based on the analysis of the quality influencing factors in the construction process of residential projects, a construction quality grade index system was established. Based on the index system, the Analytic Hierarchy Process (AHP) was used to qualitatively and quantitatively analyze various factors, combined with expert scoring. The method obtains quantitative decision-making results; the multi-index comprehensive evaluation method using artificial neural network and AHP method simulates the expert to evaluate the construction quality of residential buildings and compares the model evaluation results of construction quality with the evaluation results of experts, and analyzes artificial nerves. The case analysis of a residential project was carried out to verify the effectiveness and feasibility of the method, and the superiority of the artificial neural network in comprehensive evaluation is demonstrated.

KEYWORDS

Artificial Neural Network, Quality Evaluation, Analytic Hierarchy Process

Share and Cite:

Yue, Y. , Wu, J. , Liu, S. and Zhang, Y. (2019) Construction Quality Residential Project Based on Artificial Neural Network. Open Access Library Journal, 6, 1-10. doi: 10.4236/oalib.1105681.

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