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- 저자 : Sudong Xu (검색결과 2 건)
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Evaluation on Ecological Restoration Capability of Revetment in Inland Restricted Channel
Yimei Chen,Sudong Xu,Ying Jin 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.6
Jiangsu Province has the longest inland restricted waterway among all the provinces in China. Ecological revetment is the hot topic of current research on the river or channel regulation engineering in China. Evaluation of ecological restoration capability of revetment is an important part of revetment design as well as an effective basis of the revetment selection. Liudaxian channel of Jiangsu province is chosen for this study, an index system and method for evaluating of ecological restoration capability of revetment is established. By analyzing the mechanism and process of revetment impact on river ecosystems, indicators of ecological restoration capability and quantitative calculation method are proposed in revetment structure level. Based on the degree of influence of the indicator to river ecological function, instead of expert opinion, the set value iteration method was used to analyze the degree of influence of the indicator to river ecosystem, which made weight assignments objectively. Combining with gray relational analysis (GRA) method, the set value iteration based on ecological theory - gray correlation evaluation model was established, which achieved quantitative evaluation of the ecological restoration of revetment. The evaluating result of the projects shows that revetment of wood pile with ladder-sand tube + three-dimensional vegetation net is chosen as the recommended slope protection measure. The revetment ecological restoration evaluation model proposed in this paper with the advantages of objective, standardized and quantitative, offers an effective and feasible tool for designers and managers to evaluate the ecological restoration capability of revetment.
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An Optimal Model based on Multifactors for Container Throughput Forecasting
Shuang Tang,Sudong Xu,Jianwen Gao 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.9
Containerization plays an important role in international trade. Container throughput is a key indicator to measure the development level of a port. In this paper, Lianyungang Port and Shanghai Port are chosen to study the method for container throughput forecasting. Gray model, triple exponential smoothing model, multiple linear regression model, and backpropagation neural network model are established. Five factors are selected as influential factors. They are total retail sales of consumer goods, gross domestic product of the local city, import and export trade volume, total output value of the second industry and total fixed assets investment. The growth and the raw datasets are used in the prediction, respectively. The datasets from 1990 to 2011 are chosen to build models and the ones from 2012 to 2017 are used to assess the performance of the models. By comparison, the backpropagation neural network model is applicable to both Shanghai Port and Lianyungang Port for container throughput forecasting. The volume of container throughput at both ports from 2018 to 2020 is predicted.
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