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    APPARATUS FOR NON-DETERMINISTIC FUTURE STATE PREDICTION USING TIME SERIES DATA AND OPERATION METHOD THEREOF
    1.
    发明公开
    APPARATUS FOR NON-DETERMINISTIC FUTURE STATE PREDICTION USING TIME SERIES DATA AND OPERATION METHOD THEREOF 审中-公开

    公开(公告)号：US20240193417A1

    公开(公告)日：2024-06-13

    申请号：US18504214

    申请日：2023-11-08

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Hwin Dol PARK ,  Do Hyeun KIM ,  Jae Hun CHOI

    IPC: G06N3/08

    CPC classification number: G06N3/08

    Abstract: Disclosed is an apparatus, which includes a preprocessor that generates raw data, generates preprocessed time series data, and generates preprocessed learning data, and a learner that receives the preprocessed learning data as input data and trains a prediction model such that the similarity between a first future state predicted using the input data and a second future state predicted using data included in the same cluster as the input data increases and such that the similarity between the first future state and a third future state predicted using data included in a different cluster from the input data decreases, and the prediction model is a machine learning model for predicting a future state of the time series data at an arbitrary time point.

    DEVICE FOR PROCESSING TIME SERIES DATA HAVING IRREGULAR TIME INTERVAL AND OPERATING METHOD THEREOF
    2.
    发明申请
    DEVICE FOR PROCESSING TIME SERIES DATA HAVING IRREGULAR TIME INTERVAL AND OPERATING METHOD THEREOF 有权

    公开(公告)号：US20210319341A1

    公开(公告)日：2021-10-14

    申请号：US17229606

    申请日：2021-04-13

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Youngwoong HAN ,  Hwin Dol PARK ,  Jae Hun CHOI

    IPC: G06N5/04 ,  G06N20/00

    Abstract: Disclosed is a time-series data processing device that includes a preprocessor, a learner, and a predictor. The preprocessor generates time-series interval data based on a time interval of time-series data, generates feature interval data based on a time interval of each of features of the time-series data, and preprocesses the time-series data. The learner generates a weight group of a prediction model for generating a prediction result based on the time-series interval data, the feature interval data, and the preprocessed time-series data. The predictor generates a time-series weight, which depends on a feature weight of each of the features and a time flow of the time-series data, based on the time-series interval data, the feature interval data, and the preprocessed time-series data and generates a prediction result based on the feature weight and the time-series weight.

    DEVICE FOR ENSEMBLING DATA RECEIVED FROM PREDICTION DEVICES AND OPERATING METHOD THEREOF
    3.
    发明申请
    DEVICE FOR ENSEMBLING DATA RECEIVED FROM PREDICTION DEVICES AND OPERATING METHOD THEREOF 审中-公开

    公开(公告)号：US20200184284A1

    公开(公告)日：2020-06-11

    申请号：US16699060

    申请日：2019-11-28

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Myung-Eun LIM ,  Jae Hun CHOI ,  Youngwoong HAN

    IPC: G06K9/62 ,  G06N20/20 ,  G06N3/08 ,  G06N3/04

    Abstract: Provided is a device for ensembling data received from prediction devices and a method of operating the same. The device includes a data manager, a learner, and a predictor. The data manager receives first and second device prediction results from first and second prediction devices, respectively. The learner may adjust a weight group of a prediction model for generating first and second item weights, first and second device weights, based on the first and second device prediction results. The first and second item weights depend on first and second item values, respectively, of the first and second device prediction results. The first device weight corresponds to the first prediction device, and the second device weight corresponds to the second prediction device. The predictor generates an ensemble result of the first and second device prediction results, based on the first and second item weights and the first and second device weights.

    METHOD AND APPARATUS FOR LEARNING MULTI-LABEL ENSEMBLE BASED ON MULTI-CENTER PREDICTION ACCURACY
    5.
    发明公开
    METHOD AND APPARATUS FOR LEARNING MULTI-LABEL ENSEMBLE BASED ON MULTI-CENTER PREDICTION ACCURACY 审中-公开

    公开(公告)号：US20230316156A1

    公开(公告)日：2023-10-05

    申请号：US18057080

    申请日：2022-11-18

    Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

    Inventor： Do Hyeun KIM ,  Myung Eun LIM ,  Jae Hun CHOI

    IPC: G06N20/20

    CPC classification number: G06N20/20

    Abstract: Disclosed herein a method and apparatus for learning a multi-label ensemble based on multi-center prediction accuracy. According to an embodiment of the present disclosure, there is provided a multi-label ensemble learning method comprising: collecting a prediction value for learning data for each of a plurality of prediction models; calculating a prediction error of each of the prediction models using the prediction value of each of the prediction models and a correct answer prediction value; generating a weight label for each of the prediction models based on the prediction error; and learning an ensemble weight prediction model for predicting a weight of each of the prediction models using the weight label.

    METHOD AND APPARATUS OF ALIGNING A READ SEQUENCE
    9.
    发明申请
    METHOD AND APPARATUS OF ALIGNING A READ SEQUENCE 审中-公开
    读取序列的方法和装置

    公开(公告)号：US20140207386A1

    公开(公告)日：2014-07-24

    申请号：US13940182

    申请日：2013-07-11

    Applicant: Electronics and Telecommunications Research Institute

    Inventor： Ho-Youl JUNG ,  Minho KIM ,  Myung-eun LIM ,  Jae Hun CHOI ,  Soo Jun PARK

    IPC: G06F19/22

    CPC classification number: G16B30/00

    Abstract: Provided are a method of aligning a read sequence relative to a reference sequence using a seed and a read-sequence aligning apparatus using the same. The apparatus may include a seed generating unit producing seeds from read sequences, a representative seed selecting unit grouping the seeds into a plurality of seed clusters and selecting representative seeds from the plurality of seed clusters, a seed aligning unit aligning the representative seeds relative to a reference sequence, and a read-sequence aligning unit aligning the read sequences relative to the reference sequence, with reference to the alignment result of the representative seeds. The read sequence alignment may be performed using relationship between seeds, and thus, the sequencing may be performed with improved efficiency.

    Abstract translation: 提供了使用种子和使用其的读取序列对准装置使读取序列相对于参考序列对准的方法。 该装置可以包括从读取序列产生种子的种子生成单元，将种子分组成多个种子群并从多个种子群中选择代表性种子的代表种子选择单元，将代表性种子相对于 参考序列，以及读取序列对齐单元，参考代表性种子的比对结果，相对于参考序列对准读取序列。 可以使用种子之间的关系来执行读取序列比对，因此，可以以提高的效率进行测序。

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