Image enhancement and thresholding by optimization of fuzzy compactness
Pattern Recognition Letters
Fuzzy geometric feature-based texture classification
Pattern Recognition Letters
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
“Continuous” functions on fuzzy digital pictures
Pattern Recognition Letters
Neural network architectures for the classification of temporal image sequences
Computers & Geosciences - Special issue: neural network applications in the geosciences
Fuzzy and rule-based image convolution
Mathematics and Computers in Simulation - Special issue from the IMACS/IFAC international symposium on soft computing methods and applications: “SOFTCOM '99” (held in Athens, Greece)
Spatial decision support system for the potential evaluation of land consolidation projects
WSEAS Transactions on Computers
IEEE Transactions on Fuzzy Systems
Automatic grey level thresholding through index of fuzziness and entropy
Pattern Recognition Letters
A fuzzy operator for the enhancement of blurred and noisy images
IEEE Transactions on Image Processing
A Spatial Decision Support System design for land reallocation: A case study in Turkey
Computers and Electronics in Agriculture
Hi-index | 12.05 |
One of the most important steps of land consolidation projects is land reallocation studies. In Turkey, reallocation studies carried out in the scope of land consolidation projects are made according to farmer preferences (interviews). In addition to interview-based land reallocation model, mathematical models have been used in the previous optimization studies for reallocation procedure. Recently, fuzzy logic method, which is capable of modeling human mindset and used when other forms of mathematical models cannot be developed, has also been applied to the field of geomatic engineering, as well as in other engineering branches. This study examined the applicability of a fuzzy logic method at the reallocation stage of land consolidation study, where development of an accurate mathematical model was not possible. The results obtained from the fuzzy logic-based land reallocation model were compared with those obtained from the interview-based land reallocation model. Farmers were surveyed to determine which land reallocation model they preferred. The results indicate that 80.5% of the participant landholdings were satisfied with the fuzzy logic-based reallocation land model, while 50% were with the interview-based land reallocation model.