Abstract: The present invention provides a method for robot action imitation learning in a three-dimensional space and a system thereof, relates to the technical fields of artificial intelligence and robots. A method based on a series-parallel multi-layer backpropagation (BP) neural network is designed for robot action imitation learning in a three-dimensional space, which applies an imitation learning mechanism to a robot learning system, under the framework of the imitation learning mechanism, to train and learn by transmitting demonstrative information generated from a mechanical arm to the series-parallel multi-layer BP neural network representing a motion strategy.

Abstract: The present invention provides a takt system and method for the collaboration of production processes with uncertain time, which relates to the technical field of task collaboration. The present invention measures the collaboration efficiency of the production processes with indices such as estimated wasted time, and calculates the estimated wasted time by the expectation of the weighted sum of wasted time. For the collaboration of the production processes with uncertain time, the propagation of uncertainty factors and occurrence of wasted time in the collaborative production process are limited in a manner of takt. In different scenarios focusing on the collaboration efficiency and completion probability of the production processes, two takt control models are established, and takt solutions for the collaboration of production processes with uncertain time are obtained by solving the models.

Abstract: The present invention provides a takt system and method for the collaboration of production processes with uncertain time, which relates to the technical field of task collaboration. The present invention measures the collaboration efficiency of the production processes with indices such as estimated wasted time, and calculates the estimated wasted time by the expectation of the weighted sum of wasted time. For the collaboration of the production processes with uncertain time, the propagation of uncertainty factors and occurrence of wasted time in the collaborative production process are limited in a manner of takt. In different scenarios focusing on the collaboration efficiency and completion probability of the production processes, two takt control models are established, and takt solutions for the collaboration of production processes with uncertain time are obtained by solving the models.

Abstract: The present invention provides a method for robot action imitation learning in a three-dimensional space and a system thereof, relates to the technical fields of artificial intelligence and robots. A method based on a series-parallel multi-layer backpropagation (BP) neural network is designed for robot action imitation learning in a three-dimensional space, which applies an imitation learning mechanism to a robot learning system, under the framework of the imitation learning mechanism, to train and learn by transmitting demonstrative information generated from a mechanical arm to the series-parallel multi-layer BP neural network representing a motion strategy.

Abstract: The present invention provides a path planning method and system for self-driving of autonomous system, and relates to the technical field of autonomous systems. The method comprises following steps of: acquiring a path optimization function of an agent; converting, based on fixed-point theorems, the path optimization function of the agent into an equivalent fixed-point equation; acquiring a complete simplex sequence based on the fixed-point equation; and, determining, based on the complete simplex sequence, an initial population size and an initial position of particles for particle swarm optimization to obtain the best path planning of the agent. In the present invention, the extremal optimization of the path optimization function of the agent is converted into solving of the fixed-point equations, and initial parameters for particle swarm optimization are determined by the complete simplex sequence.

Abstract: The present invention provides a path planning method and system for self-driving of autonomous system, and relates to the technical field of autonomous systems. The method comprises following steps of: acquiring a path optimization function of an agent; converting, based on fixed-point theorems, the path optimization function of the agent into an equivalent fixed-point equation; acquiring a complete simplex sequence based on the fixed-point equation; and, determining, based on the complete simplex sequence, an initial population size and an initial position of particles for particle swarm optimization to obtain the best path planning of the agent. In the present invention, the extremal optimization of the path optimization function of the agent is converted into solving of the fixed-point equations, and initial parameters for particle swarm optimization are determined by the complete simplex sequence.

Abstract: The present invention relates to a method for identifying a preferred region for a product and an apparatus and a storage medium thereof. The method is executed by computer. The method includes: obtaining comment texts of users in different regions for a to-be-analyzed product, and extracting product features of the to-be-analyzed product from the comment texts; determining sentiment polarities of the users for the product features in the comment texts; calculating associations between sentiment orientations of the product features and the regions; extracting product features with regional preferences from the product features; and determining, for each product feature with a regional preference, a preferred region for the product feature in view of the sentiment polarities. The present invention can provide preferred regions for on-line product comments, enable enterprises to formulate more specific marketing strategies, and drive enterprises to implement regional product marketing strategies.

Abstract: The present invention relates to a method and device for on-line prediction of remaining driving mileage of an electric vehicle. The method comprises: acquiring in-transit data and driving environment data of the electric vehicle which is driving; calculating the power consumption per mileage of the electric vehicle in the current case by using the in-transit data and the driving environment data in combination with a power consumption rate data model; predicting the remaining driving mileage of the electric vehicle based on the power consumption per mileage. The device provided by the present invention is implemented on the basis of the method above. The prediction result of the present invention is more accurate, to avoid the problem that the power is exhausted due to exceeding the mileage expected by a user so that the electric vehicle cannot continue to drive, thereby improving the driving experience of the user.

Abstract: The present invention relates to a method and an apparatus for identifying a preferential region for a product. The method includes: obtaining comment texts of users in different regions for a to-be-analyzed product, and extracting product features of the to-be-analyzed product from the obtained comment texts; determining sentiment polarities of the users for the product features in the comment texts; calculating associations between sentiment orientations of the product features and the regions; extracting product features with regional preferences from the product features; and determining, for each extracted product feature with a regional preference, a preferential region for the product feature in view of the sentiment polarities. For content of fragmental and random online comments on the product, the present invention can provide a preferential region, enable an enterprise to formulate a more specific marketing strategy, and drive the enterprise to implement the regional product marketing strategy.

Abstract: The present invention relates to a method and device for on-line prediction of remaining driving mileage of an electric vehicle. The method comprises: acquiring in-transit data and driving environment data of the electric vehicle which is driving; calculating the power consumption per mileage of the electric vehicle in the current case by using the in-transit data and the driving environment data in combination with a power consumption rate data model; predicting the remaining driving mileage of the electric vehicle based on the power consumption per mileage. The device provided by the present invention is implemented on the basis of the method above. The prediction result of the present invention is more accurate, to avoid the problem that the power is exhausted due to exceeding the mileage expected by a user so that the electric vehicle cannot continue to drive, thereby improving the driving experience of the user.