Abstract: Land reallocation is one of the most important steps in
land consolidation projects. Many different models were proposed for
land reallocation in the literature such as Fuzzy Logic, block priority
based land reallocation and Spatial Decision Support Systems. A
model including four parts is considered for automatic block
reallocation with genetic algorithm method in land consolidation
projects. These stages are preparing data tables for a project land,
determining conditions and constraints of land reallocation, designing
command steps and logical flow chart of reallocation algorithm and
finally writing program codes of Genetic Algorithm respectively. In
this study, we designed the first three steps of the considered model
comprising four steps.
Abstract: In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.