الفهرس 
Architectural Spatial Layout Configuration and Fuzzy logic ApproachOnly 14 pages are availabe for public view
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Abstract
During the design phase of a project, architects strive to achieve the ideal space layout. Numerous aspects must be examined to achieve this level of optimization. Architects must consider numerous elements while designing space layouts, including dimensional characteristics such as length, width, and space orientation, as well as topological considerations such as adjacency and closeness. Architects now handle these difficulties manually by sketching space planning concepts, and then refining these designs to attain the optimal space area and proportions. In conventional spatial relation matrix diagrams, a ”strong” or ”weak” link between two spaces may be described depending on their efforts to accommodate certain constraints. These interactions are often defined generically and may exclude a broad range of characteristics and variables that might impact other spatial relationships, resulting in solutions for spatial configurations that are only partially suitable.
Space layout planning (SLP) is a challenging aspect of computer-aided architectural design (CAAD) due to the fact that the topological assignment and dimensioning of space elements must match specific criteria and limitations. The intricacy of design information and spatial relationships, as well as the stacking of multi-criteria optimization, are crucial obstacles. Thus, the application of an appropriate computational model can improve the structure of SLP via the multi-criteria decision making (MCDM) process. In this regard, fuzzy systems may be suitable for objectifying such a subjective and complex decision-making process. Lotfi A. Zadeh created fuzzy logic and set theory in 1965 as an alternative to binary logic. This method permits partial membership; values in the interval [1 - 0] from the highest level of compatibility (1) to incompatibility (0).
This research seeks to develop a computational evaluation framework based on fuzzy logic approach for architectural spatial layout configuration in order to improve the design quality of the architectural spaces. This will be accomplished by defining spatial layout configuration and afterwards establishing a preset rule for each parameter and restrictions based on fuzzy logic.
The methodology for the research includes several steps. Firstly, data collection is performed to define the space layout configuration and to define the fuzzy logic. This includes data collection to review the architectural design quality aspects and the data analysis and review of existing methods for architectural design quality evaluation tools. Secondly, different rules for architectural spatial configuration are defined as fuzzy subsets within the proposed framework of using the fuzzy logic approach for automated evaluation. Thirdly, parametric modeling software is applied to extract the spatial relations of the space layout configuration and mathematical software is used to evaluate the relations according to the predefined fuzzy logic rules. Next, the proposed approach is implemented and tested on case studies. Data analysis of the results is then performed to determine the conclusions. Finally, recommendations for future work and improvement of the proposed approach are given.
In conclusion, the proposed framework for the automated evaluation of architectural spatial layout configuration represents a significant advance in the field of architectural design evaluation. The computational methods utilized in this framework, such as fuzzy logic, offer numerous advantages over conventional approaches. The framework provides a comprehensive and systematic evaluation process that takes both measurable and subjective criteria into account, making it easier for architects and designers to make informed decisions. The automation of the evaluation process enables the efficient evaluation of a large number of plans, while the framework’s adaptability enables customization to meet specific user needs. Utilizing this framework leads to more informed, efficient, and effective design decisions, resulting in architectural spaces that are high-quality, functional, and efficient.