Evaluation of the suitability of two separate personality theories for determining user preferences in residential garden design

Landscape design is a versatile discipline that aims to enrich outdoor spaces visually, functionally and sensory-wise. Residential gardens are special outdoor areas arranged in line with individuals' personal preferences and include various usage areas. User requests and needs are important in residential garden landscaping usage preferences. In this context, the relationship between personality traits and landscape use preferences represents an important research area regarding the creation of individual and functional spaces. Research in psychology, sociology and related fields aims to understand how personality traits are shaped and how they affect an individual's life. Personality analysis is of great importance in personality-based designs. Within the scope of this study, two different personality theories that can be preferred most in order to examine the connection between personality and landscape use preferences in terms of design discipline and to conduct personality analysis are emphasized. In this study, an algorithm created with the help of artificial neural networks and two separate personality theories, the Big Five Personality Theory and Type A and Type B Personality Theory, has been presented. Within the scope of the study, a survey was conducted with participants of various gender, age and professional groups. Questions consisting of demographic characteristics, personality tests and user preferences were asked to the participants. The answers of the survey participants were evaluated as algorithm base and control data. As a result of the study, it was seen that my Type A and Type B personality theory gave more efficient results than the Big Five Personality Theory. The hypothesis of the study, whether it is possible to create an algorithm with less data, has been tested and it has been observed that among the algorithms created with data sets of 100, 200 and 400 people, the data sets of 400 people have the highest success rates. This thesis can be considered as a pioneering work for a design approach based on personality.The success and failure of the algorithms developed within the scope of the study will constitute an important reference for future landscape design studies.