- 专利标题: Forecasting routines utilizing a mixer to combine Deep Neural Network (DNN) forecasts of multi-variate time-series datasets
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申请号: US16833781申请日: 2020-03-30
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公开(公告)号: US20210303969A1公开(公告)日: 2021-09-30
- 发明人: Maryam Amiri , Petar Djukic , Todd Morris
- 申请人: Ciena Corporation
- 申请人地址: US MD Hanover
- 专利权人: Ciena Corporation
- 当前专利权人: Ciena Corporation
- 当前专利权人地址: US MD Hanover
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; H04B10/07 ; G06N3/08
摘要:
Deep Neural Networks (DNNs) for forecasting future data are provided. In one embodiment, a non-transitory computer-readable medium is configured to store computer logic having instructions that, when executed, cause one or more processing devices to receive, at each of a plurality of Deep Neural Network (DNN) forecasters, an input corresponding to a time-series dataset of a plurality of input time-series datasets. The instructions further cause the one or more processing devices to produce, from each of the plurality of DNN forecasters, a forecast output and provide the forecast output from each of the plurality of DNN forecasters to a DNN mixer for combining the forecast outputs to produce one or more output time-series datasets.