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RISFusing Data Extracted from Bridge Inspection Reports for Enhanced Data-Driven Bridge Deterioration Prediction: A Hybrid Data Fusion Method
Publisher: ASCE
Abstract: Data buried in textual bridge inspection reports offer great promise for enhanced data-driven bridge deterioration prediction. However, learning from these reports is challenging because they typically use multiple concept ...
Bridge Deterioration Knowledge Ontology for Supporting Bridge Document Analytics
Publisher: ASCE
Abstract: Bridge owners possess important data sources, such as bridge construction records and inspection and maintenance reports, which hold great promise for improving understanding of bridge deterioration and informing maintenance ...
Semantic Neural Network Ensemble for Automated Dependency Relation Extraction from Bridge Inspection Reports
Publisher: ASCE
Abstract: Bridge inspection reports are important sources of technically detailed data/information about bridge conditions and maintenance history, yet remain untapped for bridge deterioration prediction. To capitalize on these ...
Clustering-Based Approach for Building Code Computability Analysis
Publisher: ASCE
Abstract: One common limitation of all automated code compliance-checking methods and tools is their inability to deal with all types of building-code requirements. More research is needed to better identify the different types of ...
Deep Learning–Based Named Entity Recognition and Resolution of Referential Ambiguities for Enhanced Information Extraction from Construction Safety Regulations
Publisher: ASCE
Abstract: Construction safety regulations and standards contain a massive number of fall protection requirements with respect to different equipment, facilities, and operations. Automated field compliance checking aims to detect ...
Semantic Information Extraction of Energy Requirements from Contract Specifications: Dealing with Complex Extraction Tasks
Publisher: ASCE
Abstract: Automated specification energy compliance checking aims to check the compliance of building designs captured in building information models (BIMs) with energy requirements from contract specifications. However, automated ...
Deep Learning–Based Analytics of Multisource Heterogeneous Bridge Data for Enhanced Data-Driven Bridge Deterioration Prediction
Publisher: ASCE
Abstract: Existing data-driven bridge deterioration prediction methods mostly learn from abstract inventory data from a single source to predict the future conditions of bridges. Bridge inventory data [e.g., the National Bridge ...
Hierarchical Representation and Deep Learning–Based Method for Automatically Transforming Textual Building Codes into Semantic Computable Requirements
Publisher: ASCE
Abstract: Most of the existing automated compliance checking (ACC) systems are unable to fully automatically convert building-code requirements, especially requirements that have hierarchically complex semantic and syntactic structures, ...
Domain-Specific Hierarchical Text Classification for Supporting Automated Environmental Compliance Checking
Publisher: American Society of Civil Engineers
Abstract: Automated environmental compliance checking requires automated extraction of rules from environmental regulatory textual documents such as energy conservation codes and EPA regulations. Automated rule extraction requires ...
Ontology-Based Multilabel Text Classification of Construction Regulatory Documents
Publisher: American Society of Civil Engineers
Abstract: In order to fully automate the environmental regulatory compliance checking process, rules should be automatically extracted from applicable environmental regulatory textual documents, such as energy conservation codes. ...