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Found 8 papers, 2 papers with code
A Text Classification-Based Approach for Evaluating and Enhancing the Machine Interpretability of Building Codes
It is also illustrated that the proposed classification method can enhance downstream ARI methods with an improvement of 4%.
LLM-FuncMapper: Function Identification for Interpreting Complex Clauses in Building Codes via LLM
Further proof of concept in automated rule interpretation also demonstrates the possibility of LLM-FuncMapper in interpreting complex regulatory clauses.
A Multilayer Perceptron-based Fast Sunlight Assessment for the Conceptual Design of Residential Neighborhoods under Chinese Policy
This requirement is a prerequisite for obtaining a building permit during the conceptual design of a residential project.
Adaptive Control of Resource Flow to Optimize Construction Work and Cash Flow via Online Deep Reinforcement Learning
Therefore, this paper introducess a model and method to adaptive control the resource flows to optimize the work and cash flows of construction projects.
Automatic Design Method of Building Pipeline Layout Based on Deep Reinforcement Learning
The layout design of pipelines is a critical task in the construction industry.
Text Mining-Based Patent Analysis for Automated Rule Checking in AEC
Automated rule checking (ARC), which is expected to promote the efficiency of the compliance checking process in the architecture, engineering, and construction (AEC) industry, is gaining increasing attention.
Earthquake Impact Analysis Based on Text Mining and Social Media Analytics
Then, after data cleaning a series of analyses are conducted including (1) the hot words analysis, (2) the trend of the number of microblogs, (3) the trend of public opinion sentiment, and (4) a keyword and rule-based text classification for earthquake impact analysis.
Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC Domain
To this end, this work systematically explores the impacts of domain corpora and various transfer learning techniques on the performance of DL models for IR tasks and proposes a pretrained domain-specific language model for the AEC domain.
