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公开(公告)号：US20240246549A1
公开(公告)日：2024-07-25
申请号：US18003017
申请日：2022-11-28
Inventor： Shu JIANG , Hao LIU , Szu-Hao WU , Fuyang ZHAO , Xiaoyi ZHU , Haofeng KOU , Helen K. PAN
CPC classification number: B60W50/045 , B60W60/00 , B60W2050/0022 , B60W2520/10 , B60W2520/105 , B60W2556/10
Abstract: In one embodiment, a microcontroller unit (MCU) receives an expected state of an autonomous driving vehicle (ADV) from a controller of the ADV, where the controller controls motions of the ADV using a control algorithm. The MCU receives sensor data from one or more sensors of the ADV. The MCU determine an actual state of the ADV based on the sensor data. The MCU determines a performance metric of the control algorithm based on the expected state and the actual state. In response to determining the performance metric has satisfied a predetermined condition, the MCU determines a plurality of weight values for the control algorithm. The MCU sends the plurality of weight values to the control system to tune one or more weight parameters of the control algorithm using the plurality of weight values, where the controller controls the ADV using the tuned control algorithm.
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公开(公告)号：US20220082393A1
公开(公告)日：2022-03-17
申请号：US17533441
申请日：2021-11-23
IPC: G01C21/34
Abstract: A travel recommendation method, an electronic device, and a storage medium are provided, which are related to artificial intelligence, and particularly relates to fields of depth learning, map navigation and the like. The specific implementation scheme includes: obtaining a travel recommendation model according to constraint conditions and prediction conditions, wherein the constraint conditions are used for characterizing travel fairness for different types of users travelling at different moments and in different regions, and the prediction conditions are used for characterizing at least two travel modes selected by the different types of users; and obtaining travel recommendation information according to a travel target and the travel recommendation model.
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3.发明公开公开(公告)号：US20230229913A1
公开(公告)日：2023-07-20
申请号：US18125327
申请日：2023-03-23
Inventor： Weijia ZHANG , Le ZHANG , Hao LIU , Jindong HAN , Chuan QIN , Hengshu ZHU , Hui XIONG
IPC: G06N3/08
CPC classification number: G06N3/08
Abstract: A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.
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公开(公告)号：US20220101199A1
公开(公告)日：2022-03-31
申请号：US17531132
申请日：2021-11-19
Inventor： Hao LIU , Weijia ZHANG , Dejing DOU , Hui XIONG
IPC: G06N20/00
Abstract: A training method for a point-of-interest recommendation model and a method for recommending a point of interest are provided. An implementation solution includes: obtaining training data including a plurality of point-of-interest recommendation requests; determining initialization parameters of the point-of-interest recommendation model; for a first point-of-interest recommendation request among the plurality of point-of-interest recommendation requests, determining a current return for the first point-of-interest recommendation request by utilizing the point-of-interest recommendation model, and determining, based on a second point-of-interest recommendation request initiated after the first point-of-interest recommendation request is completed, a target return for the first point-of-interest recommendation request by utilizing the point-of-interest recommendation model; and adjusting the initialization parameters of the point-of-interest recommendation model based on a difference between the current return and the target return for the first point-of-interest recommendation request, to obtain final parameters of the point-of-interest recommendation model.
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公开(公告)号：US20220092433A1
公开(公告)日：2022-03-24
申请号：US17457903
申请日：2021-12-06
Inventor： Hao LIU , Jindong HAN , Hengshu ZHU , Dejing DOU
Abstract: Provided are a training method and device for a heterogeneous generative adversarial network model, an equipment, a program and a storage medium. In the training method, measurement data of a heterogeneous station is acquired, the measurement data of the heterogeneous station is set as a training sample, and joint training is performed on the heterogeneous generative adversarial network model according to a total objective function. A generator is configured to predict environment data at a future occasion according to environment data of the heterogeneous station at a historical occasion so as to output predicted data. A discriminator is configured to be input the predicted data output by the generator and corresponding measurement data, and discriminate a similarity between the measurement data and the predicted data; a total objective function includes a first objective function of the generator and a second objective function of the discriminator.
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Patent Agency Ranking
公开(公告)号：US20220092418A1
公开(公告)日：2022-03-24
申请号：US17457649
申请日：2021-12-03
Inventor： Hao LIU , Jindong HAN , Dejing DOU
Abstract: Provided are a training method for an air quality prediction model, a prediction method and apparatus, a device, a program, and a medium. The method includes the steps described below. A target monitoring range is divided into a plurality of regions; the air quality prediction model is pre-trained by adopting a pre-training sample and a pre-training objective function, where the pre-training sample includes measurement values; and the pre-trained air quality prediction model is trained by adopting a formal training sample and a formal training objective function, where the formal training sample includes the measurement values. The air quality prediction model is configured to predict air quality of the plurality of regions according to spatial information, historical information and environmental information.
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公开(公告)号：US20220082397A1
公开(公告)日：2022-03-17
申请号：US17531529
申请日：2021-11-19
Inventor： Weijia ZHANG , Hao LIU , Dejing DOU , Hui XIONG
Abstract: A method for recommending a station for a vehicle, a device, and a storage medium are provided. The method comprises: receiving, by a server, an access request from a vehicle; obtaining, based on the access request, a plurality of observation values from a plurality of stations associated with the vehicle, respectively, each observation value is based on a corresponding pre-trained recommendation model, each observation value includes factors associated with access of the vehicle to the station corresponding to the observation value; determining, an action value for the station based on the observation value and the pre-trained recommendation model for the station, the action value for the station indicates a matching degree between the access request and the station; determining a recommended station among the plurality of stations based on the action values of the plurality of stations; and sending to the vehicle an instruction of driving to the recommended station.
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公开(公告)号：US20230088445A1
公开(公告)日：2023-03-23
申请号：US18059386
申请日：2022-11-28
Inventor： Zeming LIU , Hao LIU , Zhengyu Niu , Hua WU , Haifeng WANG , Hui XIONG
Abstract: A conversational recommendation method, a method of training a conversational recommendation model, an electronic device, and a storage medium are provided, which are related to a technical field of data processing, in particular to technical fields of voice interaction, deep learning, artificial intelligence and the like. The conversational recommendation method includes: acquiring a historical conversation information; determining a target conversation object to be generated, from a conversation target graph based on the historical conversation information, the conversation target graph includes an object node, the object node is configured to represent a conversation object, and the target conversation object is determined based on the object node; and generating a target conversation information for recommendation based on the target conversation object.
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公开(公告)号：US20210108931A1
公开(公告)日：2021-04-15
申请号：US16880156
申请日：2020-05-21
Inventor： Hao LIU , Jianguo DUAN , Hui XIONG
Abstract: The present disclosure discloses a method and an apparatus for determining a hybrid travel route, a device and a storage medium, which relates to the field of intelligent transportation. The specific implementation solution is: the method includes: receiving a hybrid travel route obtaining request sent by a user terminal, where the obtaining request includes: starting point information and terminal point information; obtaining, from the cache database, travel information of each road section constituting at least one hybrid travel route, which matches the starting point information and the terminal point information; determining at least one hybrid travel route and hybrid route travel information according to the travel information of each road section; determining an optimal hybrid travel route according to travel information of each hybrid travel route; and sending the optimal hybrid travel route to the user terminal.
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公开(公告)号：US20210108930A1
公开(公告)日：2021-04-15
申请号：US16864458
申请日：2020-05-01
Abstract: The present disclosure provides a method and an apparatus for recommending a travel plan, a device and a storage medium, and relates to the field of computer technology. A query request sent by a terminal device for a travel plan is received, where the query request includes travel information. At least one candidate mixed travel plan is obtained from a travel plan database according to the travel information. A real-time travel cost parameter of the at least one candidate mixed travel plan is obtained and travel cost information of the at least one candidate mixed travel plan is obtained according to the travel cost parameter. An optimum mixed travel plan is selected from the at least one candidate mixed travel plan according to the travel cost information and sent to the terminal device. Candidate mixed travel plans are stored in the travel plan database.
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