发明名称 Weather-driven multi-category infrastructure impact forecasting
摘要 A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.
申请公布号 US9536214(B2) 申请公布日期 2017.01.03
申请号 US201615075603 申请日期 2016.03.21
申请人 INTERNATIONAL BUSINESS MACHINES CORPORATION 发明人 Heng Fook-Luen;Li Zhiguo;Siegel Stuart A.;Singhee Amith;Wang Haijing
分类号 G01W1/10;G06Q10/06;G06N5/04;G06N99/00 主分类号 G01W1/10
代理机构 Cantor Colburn LLP 代理人 Cantor Colburn LLP ;Quinn David
主权项 1. A computer implemented method of managing resources based on weather-related damage in a service area, the method comprising: selecting, by a processor, trouble regions within the service area; generating clustered regions, each of the clustered regions including at least one of the trouble regions within the service area and each of the trouble regions within the service area being associated with one of the clustered regions; training a trouble forecast model for each of the trouble regions for each type of the weather-related damage, the training for each of the trouble regions using training data from every one of the trouble regions within the clustered region associated with the trouble region, wherein the training data from each of the trouble regions within the clustered region is multiplied by a different scaling factor; applying the trouble forecast model for each of the trouble regions within the service area for each type of the weather-related damage to obtain a trouble forecast for each of the trouble regions within the service area for each type of the weather-related damage; determining a trouble forecast for the service area for each type of the weather-related damage based on the trouble forecast for each of the trouble regions within the service area; and determining a job forecast for the service area based on the trouble forecast for the service area according to a trouble-to-job mapping, wherein the managing resources is based on the job forecast for the service area, the applying the trouble forecast model for each of the trouble regions includes spatially interpolating weather forecast information within the respective trouble region to a centroid of the respective trouble region to obtain interpolated data and computing scoring input features from the interpolated data that are used to determine the trouble forecast for the respective trouble region.
地址 Armonk NY US