A Knowledge-Based Human-Computer Interaction System for the Building Design Evaluation Using Artificial Neural Network

다국어 초록 (Multilingual Abstract)

In recent years, human factors in cooperative computation have been studied increasingly, since various application contexts are complicated and highly related to the knowledge of subject-matter experts such as health care, military, and artistic designing. Due to the difficulty of knowledge elicitation and representation, human computation always faces the challenge of human-computer interaction issues. In this regard, this paper presents a human-computer interaction system based on subject knowledge to assess the influence of architecture on urban environments. Human computation is significant in generating reasonable and effective grades based on both subjective feelings and objective indicators, avoiding subjectivity and discreteness in traditional expert reviews. The artificial neural network algorithm takes part in kernel modeling to represent the comprehensive expert knowledge and calculate scores based on objective indicators. To evaluate the usability and effectiveness of the presented methodology, a dataset including 22 accomplished projects was applied and validated. The mean absolute error of the validation data was 5.53, which shows that the presented model can achieve a high accuracy. Based on the established model, two new architectural projects in the research area were evaluated and studied. The evaluated scores tallied 68 and 73, authentically reflecting the performance of the design schemes.