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Risk Identification And Evaluation Of Green Building Based On BP Neural Network

Posted on:2019-01-03Degree:MasterType:Thesis
Country:ChinaCandidate:Z YangFull Text:PDF
GTID:2322330542960838Subject:Architecture and civil engineering
Abstract/Summary:PDF Full Text Request
The construction industry as a pillar industry in our country,the economic development of our country has played an indelible role.However,the negative effects of various construction industries are also increasing,and the problems of waste materials and environmental pollution caused by the construction of the building and its ancillary facilities need to be solved urgently.With the outbreak of the world energy crisis,countries all over the world recognize that the construction industry continues to develop at the same time,but also need to seek sustainable development of environmental protection.With the continuous development of the concept of sustainable,green building went up,whether it is resource saving and environmental advantages are highlighted,however,as a new construction mode,it also has many potential risks.Based on various kinds of risks to the construction of green buildings will encounter in the process of recognition,the establishment of index system,and on the basis of the established index system to construct BP neural network risk evaluation model,analysis and evaluation of project risk using neural network model,and draw the corresponding conclusions and recomendations,to control the risk and effect supervision,to form a reasonable risk management mode.In this paper,the risk of green building and its management are described,the risk management is decomposed into several processes,and then the process is analyzed,and then the principle of BP neural network is introduced in detail.Secondly,through the questionnaire survey of experts to understand the impact of various risks of green building engineering and analysis,identify the main risk factors.Through the establishment of evaluation index system,the expert scoring is quantified.Then,using the MATLAB tool,the first 20 samples are trained as the training data of the BP neural network,and the latter 5 samples are tested as the test data.The test results show that the risk assessment model is effective.Finally,combined with the actual case,to be built in the "Sino German Eco Park international community(six)risk management project",the key risk factors according to the results of impact analysis,and to take corresponding measures to reduce the risk.
Keywords/Search Tags:green building, risk management, risk factors, BP neural network
PDF Full Text Request
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