Fuzzy expert system for land reallocation in land consolidation

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.

[1]  Mark Gahegan,et al.  Neural network architectures for the classification of temporal image sequences , 1996 .

[2]  Yasar Ayranci A Method for the Construction of a New Reallocation Plan in Land Consolidation and its Application , 2009 .

[3]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[4]  Carl G. Looney Fuzzy and rule-based image convolution , 2000 .

[5]  Tayfun Cay,et al.  Effects of different land reallocation models on the success of land consolidation projects: Social and economic approaches , 2010 .

[6]  Adapting neural networks for modelling structural behavior in geodetic deformation monitoring , 2004 .

[7]  J. Mendel Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[8]  Fangju Wang,et al.  Fuzzy supervised classification of remote sensing images , 1990 .

[9]  Akira Nakamura "Continuous" functions on fuzzy digital pictures , 1996, Pattern Recognit. Lett..

[10]  Bidyut Baran Chaudhuri,et al.  Fuzzy geometric feature-based texture classification , 1993, Pattern Recognit. Lett..

[11]  Sankar K. Pal,et al.  Automatic grey level thresholding through index of fuzziness and entropy , 1983, Pattern Recognit. Lett..

[12]  Michio Sugeno,et al.  An Approach to Linguistic Instruction Based Learning , 1993, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[13]  Petr Sklenicka,et al.  APPLYING EVALUATION CRITERIA FOR THE LAND CONSOLIDATION EFFECT TO THREE CONTRASTING STUDY AREAS IN THE CZECH REPUBLIC , 2006 .

[14]  T. Çay,et al.  Application of Fuzzy Logic in Land Consolidation Activities , 2010 .

[15]  I. Kanellopoulos,et al.  Land-cover discrimination in SPOT HRV imagery using an artificial neural network - a 20-class experiment , 1992 .

[16]  Abraham Kandel,et al.  Complex fuzzy logic , 2003, IEEE Trans. Fuzzy Syst..

[17]  田中 英夫 Masatoshi Sakawa著, Fuzzy Sets and Interactive Multiobjective Optimization, ・出版社 Plenum Press (New York and London), ・発行 1993年, ・B5判, 308頁, $78.00 , 1993 .

[18]  Giovanni Ramponi,et al.  A fuzzy operator for the enhancement of blurred and noisy images , 1995, IEEE Trans. Image Process..

[19]  S. Gün Legal State of Land Consolidation in Turkey and Problems in Implementation , 2003 .

[20]  Abraham Kandel,et al.  Fuzzy Expert Systems , 1991 .

[21]  Gour C. Karmakar,et al.  A generic fuzzy rule based image segmentation algorithm , 2002, Pattern Recognit. Lett..

[22]  Yosef S. Sherif,et al.  Applications of fuzzy set theory , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[23]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[24]  Wei Su,et al.  Spatial decision support system for the potential evaluation of land consolidation projects , 2008 .

[25]  Arvo Vitikainen,et al.  An Overview of Land Consolidation in Europe , 2004 .

[26]  Azriel Rosenfeld,et al.  Image enhancement and thresholding by optimization of fuzzy compactness , 1988, Pattern Recognit. Lett..

[27]  Musa Avci,et al.  A New Approach Oriented to New Reallotment Model Based on Block Priority Method in Land Consolidation , 1999 .

[28]  A FUZZY LOGIC APPROACH TO THE GINZBURG IV PROJECTION , 2005 .

[29]  J. Key,et al.  Classification of merged AVHRR and SMMR Arctic data with neural networks , 1989 .

[30]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.