AI knowledge model on comfort and safety in a housing complex
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This paper demonstrates an Artificial Intelligence (AI) knowledge model based on post-occupancy evaluation of a large residential housing complex. Artificial Neural Network (ANN) and Genetic Algorithm (GA) were used to create a knowledge model for residences' preferences regarding comfort and safety issues. A questionnaire regarding comfort and safety issues of the existing building and residents' opinion and their ideal expectations were collected. A five-point scale was used to depict the range of importance from least to most for each issue. A General Regression Neural Networks (GRNN) model was trained and evaluated in order to determine the best representative response for each question. The questionnaire dealing with various issues related to the safety and comfort were grouped into various grouping for GA optimization, and creating various scenarios to improve safety and comfort for the studied housing complex. Using ANN and GA, this paper has come up with a mechanism which offers a range of scenarios to show the degree of comfort and safety the builder can accomplish and the outlay he/she need to bear for the same. 2003, Civil-Comp Ltd.
