Abstract
Mosquitoes pose a significant threat to public health as vectors of various diseases. Understanding and ranking the living environments that support mosquito populations are crucial for effective mosquito control strategies. This abstract presents a novel approach using intuitionistic fuzzy sets to rank mosquito living environments based on multiple factors affecting their suitability for mosquito proliferation. The proposed methodology utilizes intuitionistic fuzzy sets to handle the uncertainties and vagueness inherent in mosquito habitat characteristics. Various environmental factors such as temperature, humidity, vegetation density, proximity to water sources, and human activities are considered input parameters for the ranking system. Each factor is assessed using linguistic variables and membership functions, capturing the degrees of truth and falsity associated with the suitability of a specific environment. By incorporating the concept of hesitancy, the ranking system allows for a more comprehensive representation of the uncertainty in mosquito habitat evaluation. The intuitionistic fuzzy sets provide a means to express not only the degree of membership but also the non-membership and hesitancy degrees associated with each environmental factor. To validate the proposed ranking system, field surveys, and expert evaluations are conducted in different geographical regions with varying mosquito species and prevalent diseases. Data collected from these surveys are used to establish membership and non-membership functions for each environmental factor. The intuitionistic fuzzy ranking approach is then applied to determine the suitability rankings of the mosquito living environments. The proposed approach offers a valuable tool for decision-makers and public health agencies involved in mosquito control programs. By utilizing intuitionistic fuzzy sets, the ranking system provides a more robust and flexible framework for assessing mosquito living environments. It enables a better understanding of the uncertainties involved in mosquito habitat evaluation and assists in prioritizing resources for effective mosquito control and disease prevention strategies.
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References
Gu W, Utzinger J, Novak RJ, Zhu H (2008) Relationships between the abundance of adult mosquitoes and environmental factors in urban and suburban areas of Guangzhou. China J Vector Ecol 33(1):89–98
Dieng H, Rahman G, Abu Hassan A, Satho T, Miake F, Boots M, Zuharah WF (2012) The effects of simulated rainfall on immature population dynamics of Aedesalbopictus and female oviposition. Int J Biometeorol 56(1):113–120
Rochlin I, Turbow D, Gomez F (2013) Ninety years after the 1923 outbreak of dengue fever in New York: reflections on the dengue threat to the United States and the need for a national surveillance and control strategy. Vector-Borne Zoonotic Dis. 13(6):369–373
Nyasembe VO, Teal PE, Sawa P, Tumlinson JH, Borgemeister C (2014) Development and survival of two major malaria vectors, Anopheles arabiensis and Anopheles funestus (Diptera: Culicidae), in desiccating soil. J Med Entomol 51(6):1275–1286
Chaves LF, Koenraadt CJ (2016) Climate change and highland malaria: fresh air for a hot debate. Q Rev Biol 91(3):225–247
Reiner Jr RC, Perkins TA, Barker CM, Niu T, Chaves LF, Ellis AM, Nisalak A (2016) A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010. J R Soc Interface 10(81):20120921
Ruiz-Moreno D, Vargas IS, Olson KE, Harrington LC (2016) Modeling dynamic introduction of Chikungunya virus in the United States. PLoS Negl Trop Dis 10(8):e0004778
Schäffer S, Früh L, Seitz F (2017) The influence of weather on Aedesalbopictus egg abundance in rubber tree holes in northern Vietnam. J Vector Ecol 42(1)
Kienberger S, Fuchs S, Höfle B (2019) Modeling the risk of mosquito-borne diseases based on remotely sensed environmental factors and social indicators. Int J Environ Res Publ Health 16(16):2954
Degefa T, Zewdie O, Berlie Y, Ademe M (2020) Spatio-temporal distribution of malaria and associated factors in Ethiopia. Parasit Vect 13(1):1–11
Cai G, Hu Q, Wang H, Wei C (2013) Intuitionistic fuzzy information aggregation in decision making. J Intell Fuzzy Syst 24(3):429–436
Wu H, Zeng X, Wang X, Zhou Z (2014) Group decision making with intuitionistic fuzzy preference relations based on TOPSIS. Int J Comput Intell Syst 7(4):724–738
Wang G, Wu X (2015) The generalized intuitionistic fuzzy Shapley value for fuzzy games. Int J Intell Syst 30(8):920–938
Wei G, Li Z (2016) Generalized intuitionistic fuzzy Choquet integral operator: aggregation operators and their applications. Soft Comput 20(5):1867–1880
Zeng X, Wu H (2017) Intuitionistic fuzzy consensus model for group decision making with incomplete preference information. Int J Intell Syst 32(1):78–96
Wang G, Wu X (2018) Intuitionistic fuzzy Hamacher weighted aggregation operators in multiple attribute decision making. Int J Comput Intell Syst 11(1):1051–1065
Dutta S, Pramanik S (2019) Generalized intuitionistic fuzzy information measure and its applications in decision-making. Int J Intell Syst 34(4):622–642
Zhang C, Chen X (2020) Intuitionistic fuzzy soft set based on distance measure and its application in decision making. Int J Intell Syst 35(5):875–892
Jiang W, Wei G, Cao J (2021) Intuitionistic fuzzy correlation analysis and its application in decision-making problems. IEEE Access 9:70801–70814
Mondal S, De S (2022) Generalized intuitionistic fuzzy rough set approximations and their application to decision making. Knowl Based Syst 239:107654
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Rajaprakash, S., Basha, C.B., Subapriya, V., Karthik, K., Jagadeesan, J., Ganesh, S.S. (2024). Ranking the Mosquito Species Habitats Using the Intuitionistic Fuzzy Analytical Hierarchy Process. In: Nagar, A.K., Jat, D.S., Mishra, D.K., Joshi, A. (eds) Intelligent Sustainable Systems. WorldS4 2023. Lecture Notes in Networks and Systems, vol 817. Springer, Singapore. https://doi.org/10.1007/978-981-99-7886-1_25
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DOI: https://doi.org/10.1007/978-981-99-7886-1_25
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