ion and classification is put forward for periodic cyclic nonstationary vibration signal. The proposed method is applied to experimental data of an ISUZU C240 diesel engine. Experiment results show the effectiveness ...ion and classification is put forward for periodic cyclic nonstationary vibration signal. The proposed method is applied to experimental data of an ISUZU C240 diesel engine. Experiment results show the effectiveness of the proposed method in classification of engine faults.展开更多
We improve inverse reinforcement learning(IRL) by applying dimension reduction methods to automatically extract Abstract features from human-demonstrated policies,to deal with the cases where features are either unkno...We improve inverse reinforcement learning(IRL) by applying dimension reduction methods to automatically extract Abstract features from human-demonstrated policies,to deal with the cases where features are either unknown or numerous.The importance rating of each abstract feature is incorporated into the reward function.Simulation is performed on a task of driving in a five-lane highway,where the controlled car has the largest fixed speed among all the cars.Performance is almost 10.6% better on average with than without importance ratings.展开更多
文摘ion and classification is put forward for periodic cyclic nonstationary vibration signal. The proposed method is applied to experimental data of an ISUZU C240 diesel engine. Experiment results show the effectiveness of the proposed method in classification of engine faults.
文摘We improve inverse reinforcement learning(IRL) by applying dimension reduction methods to automatically extract Abstract features from human-demonstrated policies,to deal with the cases where features are either unknown or numerous.The importance rating of each abstract feature is incorporated into the reward function.Simulation is performed on a task of driving in a five-lane highway,where the controlled car has the largest fixed speed among all the cars.Performance is almost 10.6% better on average with than without importance ratings.
