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11.发明申请公开(公告)号：US20180357684A1
公开(公告)日：2018-12-13
申请号：US16104088
申请日：2018-08-16
Applicant: Hefei University of Technology
Inventor： Qiang ZHANG , Shanlin YANG , Anning WANG , Zhanglin PENG , Xin Ni , Minglun REN , Xiaonong LU
CPC classification number: G06Q30/0282 , G06F17/2785
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.
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公开(公告)号：US20180136974A1
公开(公告)日：2018-05-17
申请号：US15809993
申请日：2017-11-10
Applicant: Hefei University of Technology
Inventor： Shanlin YANG , Shuai DING , Wenjuan FAN , Hao WANG , Jinxin PAN , Shikang HU , Hui HUANG
CPC classification number: G06F9/4881 , G06F19/325 , G06F19/3418 , G16H40/20
Abstract: The present invention discloses a task scheduling system and method suitable for mobile health, the characteristics thereof including: a mobile health task distribution module, a plurality of mobile health task processing modules and a mobile health task callback module; the mobile health task distribution module comprises: a resource description unit, a resource scheduling unit, a resource matcher; each of the mobile health task processing modules comprises: a task decomposition unit, a task execution unit, a task evaluation unit. The present invention is capable of carrying out tasks with full use of the currently available task processing resources, thereby being capable of improving the efficiency and performance of the task scheduling processing in the mobile health environment.
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13.发明申请公开(公告)号：US20170337646A1
公开(公告)日：2017-11-23
申请号：US15597598
申请日：2017-05-17
Applicant: Hefei University of Technology
Inventor： Kaile ZHOU , Xinhui LU , Shanlin YANG , Li SUN , Chi ZHANG , Zhen SHAO
CPC classification number: G06Q50/06 , B60L11/1824 , B60L11/1861 , G06Q10/06314 , Y02B10/14 , Y02E40/76 , Y04S10/545
Abstract: A charging and discharging scheduling method for electric vehicles in microgrid under time-of-use price includes: determining the system structure of the microgrid and the characters of each unit; establishing the optimal scheduling objective function of the microgrid considering the depreciation cost of the electric vehicle (EV) battery under time-of-use price; determining the constraints of each distributed generator and EV battery, and forming an optimal scheduling model of the microgrid together with the optimal scheduling objective function of the microgrid; determining the amount, starting and ending time, starting and ending charge state, and other basic calculating data of the EV accessing the microgrid under time-of-use price; determining the charge and discharge power of the EV when accessing the grid, by solving the optimal scheduling model of the microgrid with a particle swarm optimization algorithm.
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14.发明公开公开(公告)号：US20240005532A1
公开(公告)日：2024-01-04
申请号：US18346331
申请日：2023-07-03
Applicant: Hefei University of Technology
Inventor： Xiaojian LI , Ling LI , Shanlin YANG , Youtong TANTAI , Jin FANG , Jieyu ZHENG , Shuai DING , Lin ZHANG , Yanwei QU , Hua TANG , Liangkuan BI
CPC classification number: G06T7/248 , G06T7/74 , G06T7/50 , G06T7/60 , G06T3/0006 , G06V10/462 , G06T2207/10024 , G06T2207/10028 , G06T2207/10068 , G06T2207/30004
Abstract: Dynamic tracking methods for an in-vivo three-dimensional key point and an in-vivo three-dimensional curve can include mapping a first local region to a first local point cloud and mapping a second local region to a second local point cloud according to a mapping relation between an endoscopic image and the point clouds; determining a first three-dimensional key point of a first two-dimensional key point on the first local point cloud, and acquiring a second three-dimensional key point on the second local point cloud through a coordinate transformation; and mapping the second three-dimensional key point back to the second local region, so as to acquire a second two-dimensional key point from a next image; and acquiring two-dimensional coordinates of a tracked key point by minimizing a preset optimization function in combination with an initial two-dimensional key point, and finally acquiring corresponding three-dimensional coordinates.
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公开(公告)号：US20210234387A1
公开(公告)日：2021-07-29
申请号：US17230952
申请日：2021-04-14
Applicant: Hefei University of Technology
Inventor： Kaile ZHOU , Zenghui ZHANG , Shanlin YANG , Jianling JIAO , Xinhui LU
IPC: H02J7/00 , G01R31/382 , G01R31/392
Abstract: Provided are a method and a system for optimizing charging and discharging behaviors of a BESS based on a SOH, relating to charging and discharging optimization. The number of cycles of the battery pack and corresponding DODs are obtained based on the curve of the SOC of the battery pack. Then, the SOH of the battery pack is obtained. A charging index sequence and a discharging index sequence of battery packs are obtained based on the SOH, the SOC and a charging and discharging state of the battery pack. The optimal number of the charging and discharging battery packs and optimal DODs are determined. Charging and discharging tasks are carried out according to the charging and discharging index sequences of the battery packs based on the optimal number of the charging and discharging battery packs and the optimal DODs.
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Patent Agency Ranking
公开(公告)号：US20190041839A1
公开(公告)日：2019-02-07
申请号：US16053994
申请日：2018-08-03
Applicant: Hefei University of Technology
Inventor： Qiang ZHANG , Shanlin YANG , Wanying WANG , Zhanglin PENG , Xiaonong LU , Jun PEI
IPC: G05B23/02
Abstract: Disclosed is an apparatus for troubleshooting fault component in equipment and a method thereof. The device includes portions for building a fault-component-sensor Bayesian belief network model by acquiring component state-abnormal and data of fault maintenance of the equipment, and for calculating probabilities of actual component abnormality when a sensor connected with an component detects component abnormality based on the model; and arranging the probabilities in a descending order to obtain the arranged probabilities of actual component abnormality, and the top-arranged component being the one to be troubleshot first. Namely, a relational expression among the fault, the component and the sensor may be systematically built by adopting the method or the apparatus provided by the present disclosure, and the most-likely-failing component in an equipment may be quickly detected according to the expression, thereby improving troubleshooting efficiency.
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17.发明申请公开(公告)号：US20180342167A1
公开(公告)日：2018-11-29
申请号：US15953881
申请日：2018-04-16
Applicant: Hefei University of Technology
Inventor： He LUO , Guoqiang WANG , Zhengzheng LIANG , Xiaoxuan HU , Shanlin YANG , Huawei MA , Wei XIA , Peng JIN , Moning ZHU , Yanqiu NIU , Xiang FANG
Abstract: The embodiments of the present invention disclose a method and apparatus for joint optimization of multi-UAV task assignment and path planning. The method comprises: obtaining the location information of a plurality of UAVs and a plurality of target points, the dispersion of groundspeed course angle, and motion parameters of each UAV and wind field; constructing an initial population based on the location information, the dispersion of groundspeed course angle and a preset genetic algorithm; determining the flight status of each UAV and the flight time taken by each UAV to complete a path segment of the corresponding Dubins flight path based on the initial population and the motion parameters, obtaining the total time taken by all the UAVs corresponding to each chromosome to complete the task based on the flight time of the path segment; and subjecting the chromosomes in the initial population to crossover and mutation based on the genetic algorithm and, when a predetermined number of iterations is reached, selecting the optimal Dubins flight path as the joint optimization result. In the embodiments of the present invention, the UAV flight path planning problem is combined with the actual flight environment of the UAV, so that the optimal flight path obtained is superior to the solution in which the UAV speed is constant.
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18.发明申请公开(公告)号：US20180322954A1
公开(公告)日：2018-11-08
申请号：US15972121
申请日：2018-05-05
Applicant: Hefei University of Technology
Inventor： Shuai DING , Shanlin YANG , Xiao SUN , Shikang HU , Hao WANG
CPC classification number: G16H50/20 , G06F17/278 , G16H10/60 , G16H50/70
Abstract: The present invention discloses a method and a device for constructing a medical knowledge graph and an assistant diagnosis method. The assistant diagnosis method based on a medical knowledge graph comprises the steps of: acquiring complaint data and examination data of a patient and processing the data to obtain symptom entities and sign entities of the patient; searching, from the medical knowledge graph, disease entities associated with the symptom entities and the sign entities, calculating a posterior probability of each disease entity separately under a set of its corresponding symptom entities and sign entities; and outputting a disease entity with a maximum posterior probability as well as data corresponding to its associated nodes. The present invention provides an intelligent assistant diagnosis for clinical medicine to reduce the work burden of medical staff, relieve the medical pressure and reduce medical accidents.
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公开(公告)号：US20180197192A1
公开(公告)日：2018-07-12
申请号：US15866439
申请日：2018-01-09
Applicant: Hefei University of Technology
Inventor： Qiang ZHANG , Shanlin YANG , Anning WANG , Zhanglin PENG , Xin Ni , Minglun REN , Xiaonong LU
IPC: G06Q30/02
CPC classification number: G06Q30/0205 , G06Q30/0201 , G06Q30/0203
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.
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20.发明申请公开(公告)号：US20180118033A1
公开(公告)日：2018-05-03
申请号：US15794989
申请日：2017-10-26
Applicant: Hefei University of Technology
Inventor： Xiaonong LU , Qiang ZHANG , Wanying WANG , Anning WANG , Shanlin YANG , Minglun REN , Zhanglin PENG
CPC classification number: B60L3/12 , B60L11/1861 , B60L2240/12 , B60L2240/421 , B60L2240/547 , B60L2240/549 , B60L2240/62 , B60L2240/64 , B60L2240/662 , B60L2260/52 , B60L2260/54
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.
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