Journal of Technology in Architecture, Design and Planning
Decision Support Systems
The subject for the first issue of the Journal of Technology in Architecture, Design, and Planning of the Faculty of Architecture is entitled "Decision Support Systems." The main objective of this issue is to discuss the use of computational approaches in architectural and urban studies.
Decision-making is a process that includes people's cognitive abilities in terms of learning, reasoning, and critical thinking. The goal is to make the most appropriate decision in complex or uncertain problems. In most cases, the decision-making process is based on the experience of the expert. The expert encounters difficulties in changing conditions, which requires the support of computational systems. Decision Support Systems (DSS) are the systems that support experts in the cognitive process of decision-making. The use of DSS in solving complex and ill-defined problems of different disciplines is becoming widespread in parallel with the development of information, communication, and knowledge technologies. Decision Support Systems assist the expert by offering alternatives through artificial intelligence specialized for a particular problem. DSS is a computer program that takes as input the relevant knowledge used by the expert to find the best-fit solutions for the problem and produce results.
A decision support system consists of three components: a knowledge base containing data and data manipulation procedures; a user interface; and a problem processing subsystem, which links and coordinates models and knowledge. DSS can automatically integrate the Knowledge Discovery Process (KDP) to extract knowledge from the collected data. Different data analysis approaches (such as data mining and Bayesian networks) can be applied to generate a knowledge base for decision-making. Data mining techniques reveal the data associations and patterns. The other knowledge discovery approach BBN is used for analyzing relationships based on conditional dependency. The Analytic Hierarchy Process (AHP) method is among the most used multi-criteria decision-making methods. The Analytical Hierarchy Process (AHP) method determines criterion weights and prioritizes alternatives. AHP is an effective tool for complex decisions by setting priorities to achieve the best-fit alternatives.
Although many statistical tools and techniques are available, their scope is limited because they fail to address the uncertainty aspect of data. Many architectural and engineering problems can be tackled with artificial intelligence methods. Examples of first-generation AI-based methods are knowledge-based systems, expert systems, and case-based reasoning approaches. These systems can aid decision-making using rule-based reasoning. System performance can be significantly affected by decision rules, which are often subjectively determined by experts in the field and cannot be dynamically updated. Because of their performance are often unsatisfactory, intelligent computational methods come to the fore.
Computational intelligent systems (e.g., cellular automata, multi-agent systems, artificial neural networks, fuzzy logic, genetic algorithms, and swarm intelligence) can be used for modeling solutions in decision support systems. The scope of the decision-making applications has a wide range in urban, architecture, engineering and design domains in different scale and topics: Regional and urban planning, land use planning, urban management, facility selection, transportation, environmental, structural, building, interior, industrial design and evaluation. Within the scope of this issue, articles presenting different computational tools, technologies, methods, and applications for decision-making in different fields are expected.
As the guest editor of the first issue of the Journal of Technology in Architecture, Design, and Planning, I would like to express my sincere gratitude for the invitation to Dean, Prof. Dr. Kutgün Eyüpgiller. I hope this journal will be a platform for sharing information and discussion for academicians, researchers, and practitioners in this context.
Prof. Dr. Gülen Çağdaş, Guest Editor (Emeritus, ITU)
Gülce Kırdar, Co-Editor (MArch., ITU)