中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

179 records (took 0.055 seconds)

    VERIFYING A ROAD NETWORK OF A MAP
    71.
    发明申请
    VERIFYING A ROAD NETWORK OF A MAP 审中-公开

    公开(公告)号：US20160290813A1

    公开(公告)日：2016-10-06

    申请号：US15182660

    申请日：2016-06-15

    Applicant: International Business Machines Corporation

    Inventor： Ning Duan ,  Peng Gao ,  Baohua Wang ,  Xin Zhang

    IPC: G01C21/32 ,  G01C21/30

    CPC classification number: G01C21/32 ,  G01C21/20 ,  G01C21/26 ,  G01C21/30 ,  G01C21/34 ,  G01C21/3667

    Abstract: The present disclosure relates to a computer implemented method, a computer program product, and a computer system for verifying the road network of map. An embodiment of the present invention provides a method for verifying a road network of a map. The method comprises: determining, based on locations of a set of points in the map, a trajectory distance of a trajectory between a start point and an end point in the set of points on the map; determining a route distance between the start point and the end point in the road network of the map; and verifying the road network by comparing the trajectory distance and the route distance.

    GENERATING A TRAINING MODEL BASED ON FEEDBACK
    72.
    发明申请
    GENERATING A TRAINING MODEL BASED ON FEEDBACK 有权
    根据反馈生成培训模型

    公开(公告)号：US20150074021A1

    公开(公告)日：2015-03-12

    申请号：US14025208

    申请日：2013-09-12

    Applicant: International Business Machines Corporation

    Inventor： Liangliang Cao ,  Ning Duan ,  Qian Lin ,  Chen Wang ,  Junchi Yan ,  Xin Zhang

    IPC: G06N99/00 ,  G06N7/00

    CPC classification number: G06N3/08 ,  G06F12/06 ,  G06F17/30038 ,  G06N3/088 ,  G06N5/02 ,  G06N5/025 ,  G06N7/023 ,  G06N99/005 ,  G06Q30/02

    Abstract: A method and apparatus for generating a training model based on feedback are provided. The method for generating a training model based on feedback, includes calculating an eigenvector of a sample among a plurality of samples; obtaining scores granted by a user for one or more of the plurality of samples in a round, obtaining scores granted by the user for a first number of samples; obtaining scores granted by the user for a second number of samples in response to detecting, based on the eigenvector, an inconsistency between the scores granted by the user for the first number of samples; and generating a training model based on the scores granted by the user for the first and second numbers of samples. A corresponding apparatus is also provided.

    Abstract translation: 提供了一种基于反馈产生训练模型的方法和装置。 基于反馈生成训练模型的方法包括计算多个样本中的样本的特征向量; 获得由用户为一个或多个所述多个样本在一轮中授予的分数，获得由用户为第一数量的样本授予的分数; 响应于基于特征向量检测用户对于第一数量样本的分数的不一致性，获得用户对于第二数量样本所授予的分数; 以及基于用户为第一和第二数量样本授予的分数生成训练模型。 还提供了相应的装置。

    THERMAL AND PERFORMANCE MANAGEMENT
    73.
    发明公开
    THERMAL AND PERFORMANCE MANAGEMENT 审中-公开

    公开(公告)号：US20240004443A1

    公开(公告)日：2024-01-04

    申请号：US17852699

    申请日：2022-06-29

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

    Inventor： Xin Zhang ,  Shun Zhang ,  Shaoze Fan ,  Xiaoxiao Guo ,  Chuang Gan

    IPC: G06F1/26 ,  G06N20/00

    CPC classification number: G06F1/26 ,  G06N20/00

    Abstract: Described aspects include a system for optimizing performance of a functional circuit unit, a method of optimizing performance of a functional circuit unit, and a computer program product. In one embodiment, the system may include a functional circuit unit having an associated cooling device and power converter, one or more sensors for the functional circuit unit, the one or more sensors including a power sensor and a temperature sensor, and a first machine learning model. The first machine learning model may be adapted to receive temperature data and power data from the one or more sensors, and to generate control signals for the cooling device and the power converter to optimize performance of the functional circuit unit.

    Magnetic cores with high reluctance differences in flux paths
    75.
    发明授权
    Magnetic cores with high reluctance differences in flux paths 有权

    公开(公告)号：US11532421B2

    公开(公告)日：2022-12-20

    申请号：US17174453

    申请日：2021-02-12

    Applicant: International Business Machines Corporation

    Inventor： Yuan Yao ,  Todd Edward Takken ,  Andrew Ferencz ,  Xin Zhang ,  Liam Daley McAuliffe

    IPC: H01F27/26 ,  H02M3/335 ,  H01F41/02 ,  H01F1/147 ,  H01F27/28

    Abstract: Embodiment of the present invention includes a magnetic structure and a magnetic structure used in a direct current (DC) to DC energy converter. The magnetic structure has an E-core and a plate, with the plate positioned in contact or in near contact with the post surfaces of the E-core. The E-core has a base, a no-winding leg, a transformer leg, and an inductor leg. The no-winding leg, the transformer leg, and the inductor leg are perpendicular and magnetically in contact with the base. The plate is a flat slab with lateral dimensions generally larger than its thickness. The plate has a plate nose that overlaps a top no-winding leg surface of the no-winding leg with a no-winding gap area to form a no-winding gap with a no-winding gap reluctance. The plate also has a plate end that overlaps a top inductor leg surface of the inductor leg with an inductor gap area to form an inductor gap with an inductor gap reluctance. In some embodiments, e.g., where the duty cycle is less than 50 percent, the inductor gap reluctance will be designed to be less than the no-winding gap reluctance. In these cases, the majority of the magnetic flux that passes through the transformer leg will return through the inductor leg, instead of through the no-winding leg. The inductor and no-winding gap reluctances can he adjusted, so that the electromotive force applied to a charge passing through the inductor will partially cancel the electromotive force applied by the transformer secondary. The gap reluctance ratio can be defined, so that the difference in secondary and inductor electromotive forces is equal to the output voltage defined by an optimal no-ripple duty cycle. In this way no changing current is required through the inductor to create a dI/dt inductive voltage drop across the output inductor. Zero output current ripple is achieved.
    Various embodiments of the plate, plate shape, and no-winding leg are disclosed. These embodiments allow achieving a high ratio of no-winding gap reluctance to inductor gap reluctance, for practical, affordable magnetic material structures and aspect ratios. A high gap reluctance ratio enables zero output current ripple for the high transformer turns ratios that are needed to achieve high input to output voltage ratios. The embodiments therefore allow achieving low output current ripple for 48 V or higher input voltages, 1 V or lower output voltages, and high output currents.

    MULTI-MODAL DEEP LEARNING BASED SURROGATE MODEL FOR HIGH-FIDELITY SIMULATION
    77.
    发明申请
    MULTI-MODAL DEEP LEARNING BASED SURROGATE MODEL FOR HIGH-FIDELITY SIMULATION 有权

    公开(公告)号：US20210279386A1

    公开(公告)日：2021-09-09

    申请号：US16810687

    申请日：2020-03-05

    Applicant: International Business Machines Corporation

    Inventor： Xiaoxiao Guo ,  Xin Zhang ,  Mo Yu

    IPC: G06F30/27 ,  G06F30/28

    Abstract: A method of using multiple artificial intelligence models for generating a high fidelity simulation includes generating, by a computing device, multiple artificial intelligence models. Each artificial intelligence model simulating an industry design process. The computing device further fusing the multiple artificial intelligence models to generate a best-fit proposed industry design process. The computing device utilizes a physics constraint model to determine whether the best-fit proposed industry design process is feasible. The best-fit proposed industry design process is displayed in response to determining that the best-fit proposed industry design process is feasible.

Patent Agency Ranking