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Space-time disease mapping by combining Bayesian maximum entropy and Kalman filter: the BME-Kalman approach
International Journal of Geographical Information Science ( IF 5.7 ) Pub Date : 2020-07-22 , DOI: 10.1080/13658816.2020.1795177 Bisong Hu 1, 2 , Pan Ning 1 , Yi Li 3 , Chengdong Xu 2 , George Christakos 4 , Jinfeng Wang 2
International Journal of Geographical Information Science ( IF 5.7 ) Pub Date : 2020-07-22 , DOI: 10.1080/13658816.2020.1795177 Bisong Hu 1, 2 , Pan Ning 1 , Yi Li 3 , Chengdong Xu 2 , George Christakos 4 , Jinfeng Wang 2
Affiliation
In this work, a synthesis of the Bayesian maximum entropy (BME) and the Kalman filter (KF) methods, which enhances their individual strengths and overcomes certain of their weaknesses for spatiotem...
中文翻译:
结合贝叶斯最大熵和卡尔曼滤波器的时空疾病映射:BME-Kalman 方法
在这项工作中,贝叶斯最大熵 (BME) 和卡尔曼滤波器 (KF) 方法的综合增强了他们的个人优势并克服了他们在空间...
更新日期:2020-07-22
中文翻译:
结合贝叶斯最大熵和卡尔曼滤波器的时空疾病映射:BME-Kalman 方法
在这项工作中,贝叶斯最大熵 (BME) 和卡尔曼滤波器 (KF) 方法的综合增强了他们的个人优势并克服了他们在空间...