Grey Relational Analysis (GRA) as an Effective Method of Research into Social Preferences in Urban Space Planning

Abstract

The appearance of urban space is most often determined by planners, urbanists, and officials who fail to consider social preferences in the planning process. According to recent scientific research, spatial design should take into account people’s preferences with regard to its shape, as it is they who are the target audience. Moreover, legal regulations in many countries require the public’s inclusion into the space planning process. This paper outlines the legal status of the issue of social participation in spatial planning and provides an overview of the methods and techniques applied in the research into preferences. The aim of the article is to determine the strength of the relationship between the features adopted for the study using the grey system theory and to investigate the model’s behaviour for varied input data. It also presents the results of a study into the effect of geospatial features on the perception of the sense of security within urban space. The features were extracted using a heuristic method for solving research problems (i.e., brainstorming) and the survey was conducted by the point-scoring method. The survey results were processed by the grey system method according to the grey system theory (GST) of the grey relational analysis (GRA) type to yield a sequence of the strength of dependence between the analysed features. The study was conducted five times, with the order of entering the survey results being changed. The conducted analyses indicated that a change in the order of data from particular surveys applied for calculations resulted in the order of the epsilon coefficients in the significance sequences being changed. The analysis process was modified in order to obtain a stable significance sequence irrespective of the order of entering survey results in the analysis process. The analysis results in the form of a geospatial feature significance sequence provide information as to which of them have the greatest impact on the phenomenon under consideration. The research method can be applied to solve practical problems related to social participation.

Materials Selection of Thermoplastic Matrices of Natural Fibre Composites for Cyclist Helmet Using an Integration of DMAIC Approach in Six Sigma Method Together with Grey Relational Analysis Approach

“…According to Morán et al [31], grey relational analysis is a subfield of grey system theory that can be utilised to address problems including complicated interrelations between several different variables and elements. The grey relational analysis is a technique for conducting impact assessments using the grade of relation to determining the sequences of comparability and reference similarity [32][33][34][35]. For the calculations, the software version Microsoft Excel 2016 was used.…”

“…The final step was calculating the coefficients and weights allocated to the performance attributes and determining their grey relational grade (GRG). The options were ranked using the GRG [32][33][34][35]. The fifth tier was a group of prospects that recognised potential answers and were used when deciding which thermoplastic matrices would be best for the job.…”

“…The decision matrix in the multi-criteria problem was written in terms of sets of alternatives and the performance values of the attributes. The grey relational sequence is created by normalising the decision matrix and constructing the comparability sequence of characteristics [32][33][34][35]. For example, the performance value was defined using the formula below if the decision matrix contained m choices and n attributes,…”

Parameters optimization of tungsten inert gas welding process on 304L stainless steel using grey based Taguchi method

“…Grey relational analysis (GRA) is the most often utilized method in practice [31]. It employs data on the similarities and contrasts between a set of data defining the items under examination that may be rated.…”

“…The approach generates a significance sequence for the examined features with set rankings or assigned points, indicating which features have the greatest effect on the phenomena under consideration. The GRA approach is more successful than other techniques of social preference research (e.g., point scoring or ranking) since it allows for an analysis based on partial and sparse data while preserving the trustworthiness of the conclusions produced [31]. In multiple attribute decision making (MADM) situations, the study uses the grey relational analysis (GRA) approach.…”