STATE CLASSIFYING METHOD, STATE CLASSIFYING DEVICE, AND RECORDING MEDIUM

    公开(公告)号:US20190012413A1

    公开(公告)日:2019-01-10

    申请号:US16027961

    申请日:2018-07-05

    申请人: FUJITSU LIMITED

    IPC分类号: G06F17/50

    摘要: A non-transitory computer-readable recording medium stores therein a state classifying program that causes a computer to execute a process including: generating an attractor containing a plurality of points that correspond to a plurality of sets of time series data, coordinate values of each of the plurality of points being values corresponding to the sets of time series data; generating Betti number sequence data by applying a persistent homology process on the attractor; and classifying a state that is represented by the plurality of sets of time series data based on the Betti number sequence data.

    COMPUTER-READABLE RECORDING MEDIUM STORING EXPLANATORY PROGRAM, EXPLANATORY METHOD, AND INFORMATION PROCESSING APPARATUS

    公开(公告)号:US20230133868A1

    公开(公告)日:2023-05-04

    申请号:US17945102

    申请日:2022-09-15

    申请人: Fujitsu Limited

    IPC分类号: G06N20/00 G06K9/62 G06N5/04

    摘要: A recording medium storing an explanatory program for causing a computer to execute an explanatory process. The process includes: generating a plurality of pieces of data based on first data; calculating a ratio of output results, among a plurality of results output in a case that each of the plurality of pieces of data is input to a machine learning model, different from first results output in a case that the first data is input to the machine learning model; generating a linear model based on the plurality of pieces of data and the plurality of results in a case that the calculated ratio satisfies a criterion; and outputting explanatory information with respect to the first results based on the linear model.

    DATA ANALYSIS METHOD AND DATA ANALYSIS DEVICE

    公开(公告)号:US20210390623A1

    公开(公告)日:2021-12-16

    申请号:US17330411

    申请日:2021-05-26

    申请人: FUJITSU LIMITED

    IPC分类号: G06Q40/06 G06K9/00 G06F16/22

    摘要: A non-transitory computer-readable recording medium has stored therein a program that causes a computer to execute a process, the process including determining numerical values indicating features at respective timings having a predetermined time interval with respect to time-series data to be analyzed, numbers of the numerical values at the respective timings being made same, and generating an attractor related to the time-series data based on the determined numerical values.

    COMPUTER-READABLE RECORDING MEDIUM, DETECTION METHOD, AND DETECTION DEVICE

    公开(公告)号:US20190236407A1

    公开(公告)日:2019-08-01

    申请号:US16262974

    申请日:2019-01-31

    申请人: FUJITSU LIMITED

    IPC分类号: G06K9/62 G06K9/00

    摘要: A detection device adds, with regard to each of a plurality of sets of time-series data including a plurality of items, a time-shift term to at least any of the plurality of items included in each of the plurality of sets of time-series data. The detection device generates a plurality of attractors from the plurality of sets of time-series data to which the time-shift term has been added. The detection device generates a plurality of Betti sequences from each of the plurality of attractors by executing a persistent homology transformation on each of the plurality of attractors, each of the plurality of Betti sequences indicating a correspondence relationship between a Betti number and a scale value has been used for the persistent homology transformation. The detection device detects a state change in the plurality of sets of time-series data based on a time change in the plurality of Betti sequences.

    ANALYSIS METHOD, ANALYSIS DEVICE, AND RECORDING MEDIUM

    公开(公告)号:US20190012297A1

    公开(公告)日:2019-01-10

    申请号:US16028915

    申请日:2018-07-06

    申请人: FUJITSU LIMITED

    IPC分类号: G06F17/18 G06F17/16

    摘要: A non-transitory computer-readable recording medium stores therein an analysis program that causes a computer to execute a process including: dividing a Betti number sequence into a plurality of Betti number sequences, the Betti number sequence being included in a result of a persistent homology process performed on time series data, the plurality of Betti number sequences corresponding to different dimension of the Betti number sequence; and performing an analysis on each of the plurality of Betti number sequences.