Author
Lin Xiang-jin
Bio: Lin Xiang-jin is an academic researcher from Dalian University of Technology. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.
Papers
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Journal Article•
TL;DR: Based on Artificial Neural Network theory, the index of risk of submerged floating tunnel construction is distinguished, estimated and evaluated in this paper, where the total risk of construction is analyzed to establish the quantity reference index system.
Abstract: Based on Artificial Neural Network theory, the index of risk of submerged floating tunnel construction are distinguished, estimated and evaluated. The total risk of construction is analyzed to establish the quantity reference index system. It provides an effective tool for the risk management of submerged floating tunnel construction.
2 citations
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TL;DR: Based on the structural characteristics and preliminary design of submerged floating tunnel (SFT) prototype in Qiandao Lake, Wang et al. as mentioned in this paper gave the risk index system of public safety of SFT and risk assessment methods by analyzing different impact factors.
Abstract: Based on the structural characteristics and preliminary design of submerged floating tunnel (SFT) prototype in Qiandao Lake, this paper gives the risk index system of public safety of SFT and risk assessment methods by analyzing different impact factors of SFT public safety. Moreover, the public safety risk is evaluated during construction and operation of SFT prototype in Qiandao Lake by the presented analytic hierarchy process method. The results show that in spite of facing many technical problems and potential risks, these potential risks of SFT can be controlled or reduced to a minimum level with the help of reasonable design and certain measures.
14 citations
TL;DR: In this article, different influence factors about choice of project manager for highway slope treatment were analyzed, identified, quantified and evaluated, then comprehensive capacity of the manager was analyzed. And the quantified indexes of comprehensive capacity about project manager, based on the modal on artificial neural network theory, were obtained.
Abstract: To get the quantified indexes of comprehensive capacity about project manager, based on the modal on artificial neural network theory, different influence factors about choice of project manager for highway slope treatment were analyzed , identified, quantified and evaluated , then comprehensive capacity of the manager were analyzed. Such procedure provided a new method for choice of project manager for highway slope treatment.