Title:
HYBRID VEHICLE WORKING CONDITION PREDICTION METHOD BASED ON META-LEARNING
Document Type and Number:
WIPO Patent Application WO/2021/109644
Kind Code:
A1
Abstract:
A hybrid vehicle working condition prediction method based on meta-learning. A model training process is divided into two parts: pre-training executed offline and fine-tuning training executed online; the pre-training relates to implementing parallel training for various working conditions to obtain a base model having good generalization performance; the fine-tuning training combines multi-task training on the basis of a deep neural network, and relates to training for a specific working condition on the basis of the base model. The time cost is low, and the method can be applied to a model online correction link. In addition, on the basis of said process, further provided is a vehicle speed prediction model online application framework composed of three parts, i.e., offline training, online training, and real-time prediction, which can be applied to a working condition prediction task under actual traffic conditions.
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Inventors:
HE HONGWEN (CN)
CAO JIANFEI (CN)
CAO JIANFEI (CN)
Application Number:
PCT/CN2020/112611
Publication Date:
June 10, 2021
Filing Date:
August 31, 2020
Export Citation:
Assignee:
BEIJING INSTITUTE TECH (CN)
International Classes:
G06Q10/04
Foreign References:
| CN111047085A | 2020-04-21 | |||
| CN107463992A | 2017-12-12 | |||
| CN107284452A | 2017-10-24 | |||
| CN108346293A | 2018-07-31 |
Attorney, Agent or Firm:
BEIJING CHENGHUI LAW FIRM (CN)
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