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An Experimental Case Study on Fuzzy Logic Modeling for Selection Classification of Private Mini Hydropower Plant Investments in the Very Early Investment Stages in Turkey

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 864))

Abstract

One of the best ways to analyze the private hydropower plant investments is to investigate them based on their installed capacities. This paper describes a proposed only one node fuzzy rule base evaluation approach (experiment and test aim) to model the selection classification of the private mini hydropower plant investments in Turkey in the very early investment stages. In these kinds of early investment stages, the data and information is generally scarcely available in a very clear, detailed, sharp and specific conditions and statuses (hence fuzzy). The total estimated electricity generation (annual), the total estimated cost (total), the change in the average surface temperature (period) are taken into account in the current experimental Mamdani’s fuzzy inference based model. In this study, the mini hydropower plant investments’ data were mainly gathered from the official web pages of the Republic Of Turkey Energy Market Regulatory Authority and the General Directorate of State Hydraulic Works.

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Acknowledgments

The author would like to thank to Dr. Bernadetta Kwintiana Ane (conference) and Dr. Chin Luh Tan (sciFLT and Scilab 5.5.0 bug). This study would never be finalized and submitted to the conference without their consideration, guidance, and help. Please send your comments, feedbacks and criticisms to my e-mail (burakomersaracoglu@hotmail.com) in any format at any time. Your feedback will be very important and valuable for me during the development process of the models and systems for the real life applications.

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Correspondence to Burak Omer Saracoglu .

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Saracoglu, B.O. (2019). An Experimental Case Study on Fuzzy Logic Modeling for Selection Classification of Private Mini Hydropower Plant Investments in the Very Early Investment Stages in Turkey. In: Ane, B., Cakravastia, A., Diawati, L. (eds) Proceedings of the 18th Online World Conference on Soft Computing in Industrial Applications (WSC18). WSC 2014. Advances in Intelligent Systems and Computing, vol 864. Springer, Cham. https://doi.org/10.1007/978-3-030-00612-9_7

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