Research On Monitoring And Early Warning Of Construction Environment Based On Knowledge Reasoning

The construction activities of construction projects will have a serious negative impact on the natural environment,causing environmental pollution and ecological environmental damage.Carrying out environmental monitoring work during construction work,sensing the environmental conditions at the construction site in real time,making timely early warning and evaluation of adverse environmental impacts,and taking emergency management measures in advance can effectively alleviate the environmental problems and thus achieve sustainable development of the construction industry.However,the current construction environment monitoring system for construction projects is not perfect.The early warning method and emergency management is relatively simple.To this end,the thesis proposes a method for monitoring and early warning of construction engineering construction environment based on knowledge reasoning,and analyzes the theoretical and technical support needed to realize early warning and emergency management of construction environment.The main research contents and conclusions are as follows:Firstly,a construction environmental monitoring indicator system is initially established by analyzing and summarizing the construction environmental monitoring indicators and environmental pollution impact factors of various engineering projects.After verified by the questionnaire survey method,a more rational and comprehensive construction environment monitoring index system is finally set up.Secondly,Ontology Web Language(OWL),Protégé software and Stanford’s seven-step method are used to model building construction environment monitoring indicators,and build an ontology model of building construction environment monitoring and early warning.The formal representation,sharing and reuse of domain knowledge can be realized through the ontology model.Thirdly,the traditional Apriori algorithm is improved by adding subjective and objective interest degrees,resulting in a constraint-based Apriori algorithm.Then,based on the improved algorithm,the association rules among construction environment monitoring indicators are mined.And an early warning model of the construction environment is designed.Normative knowledge and association rule knowledge are represented as rules in the Jena rule language.Jena reasoning machine is used to realize the early warning of construction environment based on rule reasoning on eclipse development platform.Fourthly,a case base of environmental pollution in construction is constructed.And the case based reasoning is applied to the formulation of emergency management plan for construction environmental pollution.KNN algorithm is used to complete the retrieval of construction environmental pollution cases,including extracting feature attributes,determining feature attribute weights,calculating feature attribute similarity and case similarity.The methods for reusing,revising and return of construction environmental pollution cases are clarified.Fifthly,according to the design requirements,objectives and feasibilities of the construction environment monitoring and early warning system,a construction environment monitoring and early warning system consisting of the acquisition layer,the transmission layer,the service layer and the application layer is planned and designed.