中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

1343 records (took 0.026 seconds)

    一种基于粒子群算法的输电线路绕击跳闸率测评方法
    81.
    发明申请
    一种基于粒子群算法的输电线路绕击跳闸率测评方法 审中-公开

    公开(公告)号：WO2021109633A1

    公开(公告)日：2021-06-10

    申请号：PCT/CN2020/111681

    申请日：2020-08-27

    Applicant: 广东电网有限责任公司 ,  广东电网有限责任公司佛山供电局

    Inventor： 何子兰 ,  蔡汉生 ,  刘刚 ,  陈斯翔 ,  陈道品 ,  李恒真 ,  张鸣 ,  彭涛 ,  武利会 ,  梁家盛

    IPC: G01R31/00 ,  G06N3/00

    Abstract: 一种基于粒子群算法的输电线路绕击跳闸率测评方法，搭建一个试验平台，试验平台包括冲击电压发生器（11）、数据测量分析控制模块（17）、无线电流传感器（7）、同轴电缆（24）、第一基杆塔（21）、第二基杆塔（22）、第三基杆塔（23）、避雷线一（81）、避雷线二（82）、A相线路（91）、B相线路（92）、C相线路（93），基于所建立的试验平台进行绕击跳闸率测评：将C相线路（93）连接冲击电压发生器（11），冲击电压发生器（11）连接线上环绕无线电流传感器（7），将测量数据由无线电流传感器（7）反馈给数据测量分析控制模块（17），利用绕击耐雷水平实测值，结合粒子群算法优化绕击耐雷水平理论公式，进而得到绕击跳闸率。该测评方法能有效计算西北山区土壤与气候条件下输电线路绕击跳闸率，从而实现对于输电线路与杆塔结构的绕击安全测评。

    基于效用模型的个性化诊疗方法的确定方法及系统
    82.
    发明申请
    基于效用模型的个性化诊疗方法的确定方法及系统 审中-公开

    公开(公告)号：WO2021109386A1

    公开(公告)日：2021-06-10

    申请号：PCT/CN2020/083864

    申请日：2020-04-09

    Applicant: 中国科学院自动化研究所

    Inventor： 罗冠 ,  张涵钰 ,  徐欣之 ,  何子畅 ,  胡卫明

    IPC: G16H50/20 ,  G16H50/70 ,  G06N3/00 ,  G06F17/16

    Abstract: 一种基于效用模型的个性化诊疗方法的确定方法及系统，所述确定方法包括：对历史用户病症特征数据进行预处理，得到用户特征（100）；基于粒子群算法，根据所述历史用户病症数据，构建改善方法的效用矩阵（200）；根据所述效用矩阵及所述用户特征和当前用户的需求，得到针对该当前用户的个性化诊疗方法（300）。通过对多症状特征数据进行降维和归一化处理；并通过粒子群算法构建改善方法效用矩阵；根据效用矩阵、历史用户病症数据得到总效用值，根据历史改善情况调整判断改善效果阈值；根据历史病症情况数据调整决策策略为成本最低时的阈值，从而可有效确定针对该当前用户的个性化诊疗方法。

    AUTOMATIC ROOT CAUSE ANALYSIS OF FAILURES IN AUTONOMOUS VEHICLE
    85.
    发明申请
    AUTOMATIC ROOT CAUSE ANALYSIS OF FAILURES IN AUTONOMOUS VEHICLE 审中-公开

    公开(公告)号：WO2021063486A1

    公开(公告)日：2021-04-08

    申请号：PCT/EP2019/076528

    申请日：2019-10-01

    Applicant: HUAWEI TECHNOLOGIES CO., LTD. ,  TALYANSKY, Roman

    Inventor： KISILEV, Pavel ,  DANIAL, Dorin ,  CHALOM, Edmond ,  KATZ, Michael ,  SHE, Xiaoli ,  JIN, Shuyi ,  YU, Jiawei

    IPC: G05D1/00 ,  G05B23/02 ,  B60W50/02 ,  G06N3/00

    Abstract: Automatically detecting failure root cause in an autonomous vehicle, by receiving sensor data captured during a period preceding the failure by sensor(s) deployed to sense an environment of the autonomous vehicle, analyzing the sensor data to identify object(s) in the environment, creating a failure scenario defining a time-lined motion pattern of each object, computing a feature vector comprising features extracted from an output generated by sub-systems of the autonomous vehicle during the failure scenario, applying to the feature vector machine learning classification model(s) trained with a plurality of labeled feature vectors computed for a plurality of failure scenarios and their corresponding success scenarios, identifying key features significantly contributing to an outcome of the trained machine learning classification model(s) by applying an interpretation model to the machine learning classification model(s), the feature vector(s) and/or the outcome and estimating root cause failure sub-system(s) according to its association with the key feature(s).

    SIGNAL DIMENSION REDUCTION USING A NON-LINEAR TRANSFORMATION
    87.
    发明申请
    SIGNAL DIMENSION REDUCTION USING A NON-LINEAR TRANSFORMATION 审中-公开

    公开(公告)号：WO2021049986A1

    公开(公告)日：2021-03-18

    申请号：PCT/SE2019/050867

    申请日：2019-09-13

    Applicant: TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

    Inventor： TIMO, Roy ,  BERG, Miguel ,  WERNERSSON, Niklas ,  WANG, Zhao

    IPC: G06N3/00 ,  H03M7/30 ,  H04W88/08 ,  H04B7/08 ,  H04L27/26

    Abstract: Embodiments herein e.g. discloses a method performed by a radio unit (13) for handling a number of received radio signals over an array of antennas comprised in the radio unit (13). The radio unit transforms the number of received radio signals into a number of sequences of complex symbols. The radio unit further filters the number of sequences of complex symbols by inputting the number of sequences of complex symbols into a trained computational model comprising an alternating sequence of linear and nonlinear functions and thereby obtaining a reduced number of sequences. The radio unit further transmits the reduced 10number of sequences to a baseband unit (12) over a front-haul link.

    SYSTEMS AND METHODS FOR GENERATING AND PROVIDING SUGGESTED ACTIONS
    90.
    发明申请
    SYSTEMS AND METHODS FOR GENERATING AND PROVIDING SUGGESTED ACTIONS 审中-公开

    公开(公告)号：WO2021025668A1

    公开(公告)日：2021-02-11

    申请号：PCT/US2019/044900

    申请日：2019-08-02

    Applicant: GOOGLE LLC ,  WANTLAND, Tim ,  BARNHART, Melissa Lauren ,  JACKSON, Brian L.

    Inventor： WANTLAND, Tim ,  BARNHART, Melissa Lauren ,  JACKSON, Brian L.

    IPC: G06N5/02 ,  G06N5/04 ,  G06N3/00 ,  G06F3/0488 ,  G06N3/04 ,  G06N3/08

    Abstract: A computing system can include an artificial intelligence system including one or more machine-learned models that are configured to receive a model input that includes context data, and, in response, output a model output that describes one or more semantic entities referenced by the context data. The computing system can be configured to obtain the context data during a first time interval; input the model input that includes the context data into the machine-learned model(s); receive, as an output of the machine-learned model(s), the model output that describes the one or more semantic entities referenced by the context data; store the model output in at least one tangible, non-transitory computer-readable medium; and provide, for display in a user interface during a second time interval that is after the first time interval, a suggested action with respect to the semantic entity or entities described by the model output.

Patent Agency Ranking