@article{Kartal_Soyluk_2023, title={Revision of Fuzzified Fine-Kinney Method, an Adaptive Method for Natural Disaster Risk Management}, volume={6}, url={https://oiccpress.com/geoconservation-research/article/revision-of-fuzzified-fine-kinney-method-an-adaptive-method-for-natural-disaster-risk-management/}, DOI={10.57647/j.gcr.2023.0602.25}, abstractNote={Natural disasters are rather unpredictable and can interrupt human life, cause economic damage and even take lives. Even though they are mostly unpredictable, there are methods for assessing the risks of natural disasters, one of which is the Fine-Kinney, which was originally used for assessing industrial accident risks. Even though the method has been applied to natural disasters, the results are not very rational and precise because of the dissimilarity between both phenomena. Here we adapt the Fine-Kinney method by fuzzification to produce fast and reliable results in the building environment for natural disasters, even in situations where there is limited data. Both standard and fuzzy Fine-Kinney methods are applied to the Mustafakemalpaşa district in Bursa, Turkey, as a case study. The results of this case study are compared with the risk maps provided by the local government, to prove the accuracy and reliability of the method. While both methods produced similar and reliable results when compared to the risk maps, the Fuzzy Fine-Kinney results were more realistic because of the nature of fuzzy logic.  }, number={2}, journal={Geoconservation Research (Geoconserv. Res.)}, publisher={OICC Press}, author={Kartal, Doğukan and Soyluk, Asena}, year={2023}, month={Dec.}, keywords={Risk Assessment, Natural Disasters, Fuzzy Logic, Fine-Kinney} }