使用塞拉利昂气候变化预测疟疾病例

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Updated: May 23, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

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Saidu Wurie Jalloh1,2, Boniface Malenje3, Herbert Imboga3

  • 1Department of Mathematics (Data Science Option), Pan African University Institute for Basic Sciences Technology and Innovation, Kiambu, 00200, Juja, Kenya. wurie.saidu@students.jkuat.ac.ke.

Malaria journal
|May 20, 2025
PubMed
概括

人工神经网络 (ANN) 在塞拉利昂疟疾预测方面显著优于传统的季节性自回归集成移动平均 (SARIMA) 模型. ANN提供更准确的预测,对于有效的公共卫生干预疟疾至关重要.

关键词:
人工神经网络的人工神经网络疾病监测 疾病监测疟疾:疟疾是一种疾病.公共卫生 公共卫生季节性自回归集成移动平均线塞拉利昂 塞拉利昂时间序列预测时间序列预测

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