Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/3246
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dc.contributor.authorAbisoye, Opeyemi Aderiike-
dc.contributor.authorJimoh, R.G.-
dc.date.accessioned2021-06-15T12:56:08Z-
dc.date.available2021-06-15T12:56:08Z-
dc.date.issued2018-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/3246-
dc.description.abstractOne of the most important things in life is health. Poor health condition affects one’s life span and achievement; one of such common disease is malaria. Dynamics of Malaria parasite transmission is complex and been widely studied. Research is needed to understand the factors responsible for complexity of symptomatic malaria infection changes. Several internal and external factors are responsible for malaria transmission and severity. A survey of descriptive and experimental case study design of sampled health centers was carried out in Minna Metropolis. Also climatic data was collected from Nigerian Environmental and Climate Observation Programme (NECOP) Weather Station, Bosso Campus, Federal University of Technology, Minna, Niger state. Nigeria. The malaria cases data and climatic data served as input variables. The results indicated that symptomatic malaria infection is highly influenced externally by Temperature, Rainfall and Relative humidity. The imposed threats were headache, fever, dizziness, body pain and vomiting. This Climatic data combined with monthly malaria incidences were considered as input variables, trained and simulated using Microsoft Excel and libSVM in MATLAB 2015a. Self-Organizing Map (SOM) network was used to cluster the features. From the study after training with SMO, vomiting is the most prevalence threat followed by fever, dizziness and headache. Also the major climatic factor is the rainfall followed by temperature and relative humidity. The performance of the model was evaluated with classification accuracy, sensitivity, specificity and mean square error (mse). The results gave 85.60 100% , 84.44% , and 0.0776mse.en_US
dc.language.isoenen_US
dc.publisherJournal of Science, Technology, Mathematics and Education (JOSTMED)en_US
dc.subjectMalariaen_US
dc.subjectClassificationen_US
dc.subjectSeverityen_US
dc.subjectPredictionen_US
dc.subjectTransmissionen_US
dc.subjectParasite Counten_US
dc.titleA SURVEY OF FACTORS AFFECTING SYMPTOMATIC AND CLIMATIC BASED MALARIA PARASITE COUNTSen_US
dc.typeArticleen_US
Appears in Collections:Computer Science

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