Abstract
The aim of this research is to develop an efficient system which will identify the probability of dengue occurrence in Dhaka, Bangladesh based on a neural network system and fuzzy inference algorithm. When using fuzzy inference technique, we separated the dengue cases into four quadrants of 3 months in a year. Based on dengue infection rate each quadrant is classified from high to low. An adaptive neuro based fuzzy inference system provides the insight for implementing fuzzy rules. Then we analyze the performances using fuzzy logic and ANFIS to point out the percentage of infected rate.
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Acknowledgment
The raw data set provided by IEDCR of monthly dengue cases helped us to finish this paper. We retrieved population data of Dhaka from Bangladesh Bureau of Statistics.
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Arifuzzaman, M., Faqrul Islam Shaon, M., Jahidul Islam, M., Rahman, R.M. (2016). Detection of Dengue Epidemic in Dhaka, Bangladesh by a Neuro Fuzzy Approach. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 653. Springer, Cham. https://doi.org/10.1007/978-3-319-33810-1_13
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DOI: https://doi.org/10.1007/978-3-319-33810-1_13
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