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Mekânsal Bulanık Karar Destek Sisteminin Geliştirilmesi

Year 2020, Ejosat Special Issue 2020 (ARACONF), 418 - 429, 01.04.2020
https://doi.org/10.31590/ejosat.araconf55

Abstract

Bu araştırmanın temel amacı, CBS (Coğrafi Bilgi Sistemleri) tabanlı ÇKKV (Çok Kriterli Karar Verme) yöntemleriyle bir Mekansal Karar Destek Sistemi (MKDS) geliştirmektir. MKDS, mekansal problemlerin çözümünde karar vermeye yardımcı olmak için tasarlanmış bilgisayar tabanlı bir sistemdir. Bu sistemler, karar vericilere mekânsal ve öznitelik bilgilerinin birleştirildiği çözüm uzayında çoklu mekânsal kriterleri kullanarak en uygun seçeneğin belirlenmesini sağlamaktadır. Ayrıca, raster ve konuma dayalı farklı alanlardaki bilimsel araştırmalarda sıkça tercih edilmektedir. CBS ile analizler yapılırken değerlendirme kriterlerinin birden fazla olması, süreci kompleks hale getirmektedir. Günümüzde, CBS bazlı çalışmalar kapsamında en uygun yerin belirlenmesi için, çok kriterli karar verme modelleri ile mekansal analizleri entegre ederek harita çözümünü destekleyebilecek mimariler yaygın değildir. Bu sebeple, CBS teknolojilerinin karar verme süreçlerinde mekansal karar vermeye yönelik çözümler sunabilme kapasitesi yetersizdir.

Bu kapsamda NetCAD firması ile yer seçimi ve değerlendirme amaçlı tematik haritaların yapılmasına yönelik bir model geliştirilmiş ve NetCAD Mimari Analiz modülü altında yapıyı entegre eden bir program oluşturulmuştur. Yer seçim ve değerlendirme problemlerine göre belirlenen kriterlerlerin ağırlıkları Bulanık ÇKKV metotlarından Fuzzy AHP, Fuzzy DEMATEL ve evrimsel algoritma modellerinden Fuzzy CMA-ES ile hesaplanmıştır. Problemlerde yer alan alternatiflerin seçim ve sıralama aşaması Fuzzy TOPSIS metodu ile çözümlenmiştir. Belirtilen süreçlerin tamamında CBS temelli yazılım ürünü olan NetCAD mimarda C sharp programlama dili ile kullanılarak arayüzler oluşturulmuş ve analiz modülüne entegre edilmiştir. Sonrasında, bağımsız bir değişkenin farklı ağırlık değerlerinin sonucu nasıl etkilediği duyarlık analizleri ile belirlenmiştir. Sonuç olarak, nokta, alan ve piksel bazlı tematik haritalar üretilmiştir. Raster harita şeklinde oluşturulan katmanları birleştiren ve sıralandıran TOPSIS, Bulanık TOPSIS, Weigted Overlay, WLC gibi yöntemler kullanılarak karşılaştırmalı uygunluk haritası üretilmiş ve bu haritalar üzerinde en uygun yer seçimini esas alan bir model geliştirilmiştir.

Supporting Institution

TÜBİTAK

Project Number

3170954

Thanks

Bu çalışma TUBİTAK TEYDEB 1501 Proje No:3170954 ile desteklenmektedir.

References

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  • Arentze T.A., Borgers A.W.J. & Timmerman H.J.P, (1996). Integrating GIS into planning process. In: Fisher M, Scholten HJ, and Unwin D (eds), Spatial Analytical Perspectives on GIS, pp 187–98. Taylor & Francis, London, UK.
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  • Bakhtiarifar, M., Mesgari, M. S., Karimi, M. & Chehreghani, A. (2011). Land use change modeling using multi-criteria decision analysis and GIS. Journal of Envıronmental Studıes, 37(58); 43- 52.
  • Bali, A., Monavari, S.M., Riazi, B., Khorasani, N. & Kheirkhah Zarkesh, M., (2015). A spatial decision support system for ecotourism development in Caspian hyrcanian mixed forests ecoregion. Bol. Ciênc. Geod. 21 (2), 340–353.
  • Barredo JI. (1996). Sistemas de Informaci´on Geogr´afica y Evaluaci´on Multicriterio en la ordenaci´on del territorio. Ra-Ma, Madrid, Spain.
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  • Gómez-Limón, J.A. & Riesgo, L., (2009). Alternative approaches to the construction of a composite indicator of agricultural sustainability: an application to irrigated agriculture in the Duero basin in Spain. J. Environ. Manage. 90, 3345–3362.
  • Goodchild, M.F., (1992). Geographical information science. Int. J. Geograp. Inform. Syst. 6 (1), 31–45.
  • Hassan, H. A., El-Bakry, H. M., & Allah, H. G. A. (2013). Design of Multi-Criteria Spatial Decision Support System (MC-SDSS) for Animal Production. IAES International Journal of Artificial Intelligence, 2(3), 117.
  • Jakimavičius, M., & Burinskiene, M. (2009). A GIS and multi‐criteria‐based analysisand rankingof transportation zonesof Vilniuscity. Technological and Economic Development of Economy, 15(1), 39-48.
  • Jankowski P. 1995. Integrating geographical information systems and multiple criteria decision-making methods. International J Geographical Information Systems 9:251–273.
  • Jelokhani-Niaraki, M., & Malczewski, J. (2015). A group multicriteria spatial decision support system for parking site selection problem: A case study. Land Use Policy, 42, 492-508.
  • Joerin F, Th´eriault M, & Musy A. (2001). Using GIS and outranking multicriteria analysis for land-use suitability assessment. International J Geographical Information Sci 15:153–74.
  • Johnston J. (1999). Geography and GIS. In: Longley PA, Goodchild MF, Maguire DJ, et al. (eds), Geographical Information Systems, vol II, pp 39–47. John Wiley & Sons, Inc, New York, NY, USA.
  • Johnson, M. P. (2005). Spatial decision support for assisted housing mobility counseling. Decision Support Systems, 41(1), 296-312.
  • Juan, Y. K., Roper, K. O., Castro-Lacouture, D., & Kim, J. H. (2010). Optimal decision making on urban renewal projects. Management Decision, 48(2), 207-224.
  • Lukashe A.F., Droste R.L. & Warith M.A. (2001). Review of Expert Systems (ES), Geographic Information System (GIS), Decision Support System (DSS), and their applications in landfill design and management. Waste Management & Res 19:177–85.
  • Mahdavi, A., & Niknejad, M. (2014). Site suitability evaluation for ecotourism using MCDM methods and GIS: Case study-Lorestan province, Iran. Journal of Biodiversity and Environmental Sciences, 4(6), 425-437.
  • Malczewski, J. (1996). A GIS-based approach to multiple criteria group decision-making. International Journal of Geographical Information Systems, 10(8), 955-971.
  • Malczewski, J., (1999). GIS and Multicriteria Decision Analysis. John Wiley & Sons, New York.
  • Malczewski, J. (2006). GIS‐based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703-726.
  • Malczewski, J., (2010). Multiple criteria decision analysis and geographic information systems. In: Figueira, J., Greco, S., Ehrgott, M. (Eds.), Trends in Multiple Criteria Decision Analysis. Springer, New York, pp. 369–395.
  • Mari, R., Bottai, L., Busillo, C., Calastrini, F., Gozzini, B., & Gualtieri, G. (2011). A GIS-based interactive web decision support system for planning wind farms in Tuscany (Italy). Renewable Energy, 36(2), 754-763.
  • Moghadam, S. T., Delmastro, C., Lombardi, P., & Corgnati, S. P. (2016). Towards a new integrated spatial decision support system in urban context. Procedia-Social and Behavioral Sciences, 223, 974-981.
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  • Nasehi, S., Karimi, S., & Jafari, H. (2016). Application of Fuzzy GIS and ANP for Wind Power Plant Site Selection in East Azerbaijan Province of Iran.
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Development of Spatial Fuzzy Decision Support System

Year 2020, Ejosat Special Issue 2020 (ARACONF), 418 - 429, 01.04.2020
https://doi.org/10.31590/ejosat.araconf55

Abstract

The main purpose of this research is to develop a Spatial Decision Support System (SDSS) with Geographic Information System (GIS) based Multiple Criteria Decision Making (MCDM) methods. SDSS is a computer-based system designed to assist decision making in solving a spatial problem. These systems allow decision makers to select the most suitable option using multiple spatial criteria in the solution space where spatial and attribute information are combined. Besides, it is frequently preferred in various working areas of scientific research based on raster and location. However, the fact that the evaluation criteria are more than one while making analyzes with GIS complicates the process. Today, architectures that can support the map solution that combines spatial analysis with multi-criteria decision-making models are not common to determine the most suitable location within the scope of GIS based studies. For this reason, the capacity of GIS technologies to offer solutions for spatial decision making in decision making processes is insufficient. In this context, a model for making thematic maps with Netcad company was developed in terms of location selection and evaluation and a program integrated in the NetCAD Software was produced under the NetCAD Architectural Analysis module. The weights of the criteria determined according to location selection and evaluation problems were calculated with Fuzzy AHP, Fuzzy DEMATEL, Weighted Linear Combination, Weighted Overlay and Fuzzy CMA-ES from evolutionary algorithm models. The selection and ranking stage of the alternatives in the problems was resolved with the Fuzzy TOPSIS method. Then, how different weight values of an independent variable affect the result was determined with sensitivity analysis. All of the processes mentioned were interfaced and integrated into the analysis module using C sharp programming language in NetCAD architect, which is a GIS based software product. As a result, point, area and pixel based thematic maps were produced. A comparative suitability map provided that using MCDM Methods such as TOPSIS, Fuzzy TOPSIS, Weigted Overlay, WLC which combine and sort layers in the form of a raster map was produced. Comparative suitability map production was provided by using methods and a model based on the most suitable location selection was developed on these maps.

Project Number

3170954

References

  • Antunes, P., Karadzic, V., Santos, R., Beça, P. & Osann, A., (2011). Participatory multicriteria analysis of irrigation management alternatives: the case of the Caia irrigation district, Portugal. Int. J. Agric. Sustain. 9 (2), 334–349.
  • Arentze T.A., Borgers A.W.J. & Timmerman H.J.P, (1996). Integrating GIS into planning process. In: Fisher M, Scholten HJ, and Unwin D (eds), Spatial Analytical Perspectives on GIS, pp 187–98. Taylor & Francis, London, UK.
  • Aydin, N. Y., Kentel, E., & Duzgun, H. S. (2013). GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey. Energy conversion and management, 70, 90-106.
  • Bakhtiarifar, M., Mesgari, M. S., Karimi, M. & Chehreghani, A. (2011). Land use change modeling using multi-criteria decision analysis and GIS. Journal of Envıronmental Studıes, 37(58); 43- 52.
  • Bali, A., Monavari, S.M., Riazi, B., Khorasani, N. & Kheirkhah Zarkesh, M., (2015). A spatial decision support system for ecotourism development in Caspian hyrcanian mixed forests ecoregion. Bol. Ciênc. Geod. 21 (2), 340–353.
  • Barredo JI. (1996). Sistemas de Informaci´on Geogr´afica y Evaluaci´on Multicriterio en la ordenaci´on del territorio. Ra-Ma, Madrid, Spain.
  • Boroushaki, S., & Malczewski, J. (2008). Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS. Computers & Geosciences, 34(4), 399-410.
  • Bosque-Sendra J & Garc´ıa RC. 2000. El uso de los sistemas de informaci´on geogr´afica en la planificaci´on territorial. Anales de Geograf´ıa de la Universidad Complutense 20:49– 67.
  • Carver, S. J. (1991). Integrating multi-criteria evaluation with geographical information systems. International Journal of Geographical Information System, 5(3), 321-339.
  • Chakhar, S. & Martel, J.M., (2003). Enhancing geographical information systems capabilities with multicriteria evaluation functions. J. Geograp. Inform. Decis. Anal. 7, 47–71.
  • Chakhar, S. & Mousseau, V., (2008). Generation of spatial decision alternatives based on a planar subdivision of the study area. In: Yetongnon, K., Chbeir, R., Dipanda, A. (Eds.), Advanced Internet Based Systems and Applications, Lecture Notes in Computer Science, 4879, pp. 137–148.
  • Charabi, Y. & Gastli, A. (2011). PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation. Renewable Energy, 36(9), 2554-2561.
  • Cowen, T. (Ed.). (1988). The theory of market failure: A critical examination. George Mason University Press.
  • Dai F.C., Lee C.F. & Zhang X.H. (2001). GIS-based geo-environmental evaluation for urban land-use planning: A case study. Engineering Geology 61:257–71.
  • Dantsis, T., Douma, C., Giourga, C., Loumou, A. &Polychronaki, E.A., (2010). A methodological approach to assess and compare the sustainability level of agricultural plant production systems. Ecol. Ind. 10, 256–263.
  • Dashti, S., Monavari, S. M., Hosseini, S. M., Riazi, B., & Momeni, M. (2013). Application of GIS, AHP, Fuzzy and WLC in island ecotourism development (Case study of Qeshm Island, Iran). Life Science Journal, 10(1), 1274-1282.
  • Delgado, M. G., & Sendra, J. B. (2004). Sensitivity analysis in multicriteria spatial decision-making: a review. Human and Ecological Risk Assessment, 10(6), 1173-1187.
  • Densham, P. J., & Goodchild, M. (1989). Spatial decision support systems: A research agenda. Unknown Journal, 707-716.
  • Defne, Z., Haas, K. A., & Fritz, H. M. (2011). GIS based multi-criteria assessment of tidal stream power potential: A case study for Georgia, USA. Renewable and Sustainable Energy Reviews, 15(5), 2310-2321.
  • Erden, T., & Coşkun, M. Z. (2011). Acil durum servislerinin yer seçimi: Analitik Hiyerarşi Yöntemi ve CBS entegrasyonu. İTÜDERGİSİ/d, 9(6).
  • Ertuğrul, İ., & Karakaşoğlu, N. (2008). Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. The International Journal of Advanced Manufacturing Technology, 39(7-8), 783-795.
  • Esmaelian, M., Tavana, M., Santos Arteaga, F. J., & Mohammadi, S. (2015). A multicriteria spatial decision support system for solving emergency service station location problems. International Journal of Geographical Information Science, 29(7), 1187-1213.
  • Fotheringham AS & Wegener M. (2000). Spatial Models and GIS. Taylor & Francis, London, UK.
  • Gigović, L., Pamučar, D., Lukić, D., & Marković, S. (2016). GIS-Fuzzy DEMATEL MCDA model for the evaluation of the sites for ecotourism development: A case study of “Dunavski ključ” region, Serbia. Land Use Policy, 58, 348-365.
  • Gómez-Limón, J.A. & Riesgo, L., (2009). Alternative approaches to the construction of a composite indicator of agricultural sustainability: an application to irrigated agriculture in the Duero basin in Spain. J. Environ. Manage. 90, 3345–3362.
  • Goodchild, M.F., (1992). Geographical information science. Int. J. Geograp. Inform. Syst. 6 (1), 31–45.
  • Hassan, H. A., El-Bakry, H. M., & Allah, H. G. A. (2013). Design of Multi-Criteria Spatial Decision Support System (MC-SDSS) for Animal Production. IAES International Journal of Artificial Intelligence, 2(3), 117.
  • Jakimavičius, M., & Burinskiene, M. (2009). A GIS and multi‐criteria‐based analysisand rankingof transportation zonesof Vilniuscity. Technological and Economic Development of Economy, 15(1), 39-48.
  • Jankowski P. 1995. Integrating geographical information systems and multiple criteria decision-making methods. International J Geographical Information Systems 9:251–273.
  • Jelokhani-Niaraki, M., & Malczewski, J. (2015). A group multicriteria spatial decision support system for parking site selection problem: A case study. Land Use Policy, 42, 492-508.
  • Joerin F, Th´eriault M, & Musy A. (2001). Using GIS and outranking multicriteria analysis for land-use suitability assessment. International J Geographical Information Sci 15:153–74.
  • Johnston J. (1999). Geography and GIS. In: Longley PA, Goodchild MF, Maguire DJ, et al. (eds), Geographical Information Systems, vol II, pp 39–47. John Wiley & Sons, Inc, New York, NY, USA.
  • Johnson, M. P. (2005). Spatial decision support for assisted housing mobility counseling. Decision Support Systems, 41(1), 296-312.
  • Juan, Y. K., Roper, K. O., Castro-Lacouture, D., & Kim, J. H. (2010). Optimal decision making on urban renewal projects. Management Decision, 48(2), 207-224.
  • Lukashe A.F., Droste R.L. & Warith M.A. (2001). Review of Expert Systems (ES), Geographic Information System (GIS), Decision Support System (DSS), and their applications in landfill design and management. Waste Management & Res 19:177–85.
  • Mahdavi, A., & Niknejad, M. (2014). Site suitability evaluation for ecotourism using MCDM methods and GIS: Case study-Lorestan province, Iran. Journal of Biodiversity and Environmental Sciences, 4(6), 425-437.
  • Malczewski, J. (1996). A GIS-based approach to multiple criteria group decision-making. International Journal of Geographical Information Systems, 10(8), 955-971.
  • Malczewski, J., (1999). GIS and Multicriteria Decision Analysis. John Wiley & Sons, New York.
  • Malczewski, J. (2006). GIS‐based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703-726.
  • Malczewski, J., (2010). Multiple criteria decision analysis and geographic information systems. In: Figueira, J., Greco, S., Ehrgott, M. (Eds.), Trends in Multiple Criteria Decision Analysis. Springer, New York, pp. 369–395.
  • Mari, R., Bottai, L., Busillo, C., Calastrini, F., Gozzini, B., & Gualtieri, G. (2011). A GIS-based interactive web decision support system for planning wind farms in Tuscany (Italy). Renewable Energy, 36(2), 754-763.
  • Moghadam, S. T., Delmastro, C., Lombardi, P., & Corgnati, S. P. (2016). Towards a new integrated spatial decision support system in urban context. Procedia-Social and Behavioral Sciences, 223, 974-981.
  • Mohit, M. A., & Ali, M. M. (2006). Integrating GIS and AHP for land sutiabiltiy Analysis for Urban Development in a Secondary City of Bangladesh. Jurnal alam Bina, 8(1), 1-20.
  • Mohd Shamsuddin, N. H., bin Othman, M. S., & bin Selamat, M. H. (2013). Identifying of Potential Crime Area Using Analytical Hierachy Process (AHP) and Geographical Information System (GIS). International Journal of Innovative Computing, 2(1).
  • Nasehi, S., Karimi, S., & Jafari, H. (2016). Application of Fuzzy GIS and ANP for Wind Power Plant Site Selection in East Azerbaijan Province of Iran.
  • Raju, K.S., Duckstein, L. & Arondel, C., (2000). Multicriterion analysis for sustainable water resources planning: a case study in Spain. Water Resour. Manage 14, 435–456.
  • Ray, D. (2007). A game-theoretic perspective on coalition formation. Oxford University Press.
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  • Sánchez-Lozano, J. M., Teruel-Solano, J., Soto-Elvira, P. L., & García-Cascales, M. S. (2013). Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain. Renewable and Sustainable Energy Reviews, 24, 544-556.
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There are 62 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Mithat Zeydan 0000-0001-9459-146X

Bülent Bostancı 0000-0003-2255-2503

Burcu Oralhan 0000-0001-8905-0140

Defne Eroğlu This is me 0000-0002-3195-1621

Ulaş Aydıner This is me 0000-0003-0186-6028

Project Number 3170954
Publication Date April 1, 2020
Published in Issue Year 2020 Ejosat Special Issue 2020 (ARACONF)

Cite

APA Zeydan, M., Bostancı, B., Oralhan, B., Eroğlu, D., et al. (2020). Mekânsal Bulanık Karar Destek Sisteminin Geliştirilmesi. Avrupa Bilim Ve Teknoloji Dergisi418-429. https://doi.org/10.31590/ejosat.araconf55