DETERMINING OPTIMAL MACHINE LEARNING ALGORITHMS FOR USE IN A NEURAL NETWORK

    公开(公告)号:US20220405568A1

    公开(公告)日:2022-12-22

    申请号:US17304498

    申请日:2021-06-22

    Abstract: Approaches presented herein enable determining an optimal set of machine learning algorithms for use in an artificial neural network. More specifically, a plurality of artificial neural networks is trained using a training data set. Each of the plurality of artificial neural networks has a respective unique architecture that comprises a combination of hidden layers, artificial neurons, and machine learning algorithms. Respective prediction rates of each of the plurality of artificial neural networks are compared. A best predictor artificial neural network of the plurality of artificial neural networks is identified, such that the best predictor artificial neural network has a prediction rate which is the most accurate of the respective prediction rates based on the comparing. A set of one or more machine learning algorithms used in the best predictor artificial neural network is determined.

    Drift detection in edge devices via multi-algorithmic deltas

    公开(公告)号:US11991050B2

    公开(公告)日:2024-05-21

    申请号:US18049362

    申请日:2022-10-25

    CPC classification number: H04L41/16 H04L41/0631

    Abstract: One or more systems, devices, computer program products and/or computer-implemented methods provided herein relate to data drift detection in an edge device. A system can comprise a memory configured to store computer executable components; and a processor configured to execute the computer executable components stored in the memory, wherein the computer executable components can comprise a verification component that can verify accuracy of a first model and accuracy of a second model to detect data drift associated with an edge device that is deployed without network connectivity; a computation component that can compute at least a first ratio based on the accuracy of the first model and the accuracy of the second model; and an analysis component that can use the at least the first ratio to determine whether performance degradation of at least one of the first model or the second model is a function of the data drift.

    Software developer assignment utilizing contribution based mastery metrics

    公开(公告)号:US11321644B2

    公开(公告)日:2022-05-03

    申请号:US16749015

    申请日:2020-01-22

    Abstract: Techniques for an expertise score vector for software component management are described herein. An aspect includes determining a size and an amount of time corresponding to committed code contributed by a first developer to a first software component. Another aspect includes determining a time per unit of contribution based on the size and amount of time. Another aspect includes updating component mastery metrics corresponding to the first software component in an expertise score vector corresponding to the first developer based on the time per unit of contribution. Another aspect includes assigning the first developer to a developer tier based on the component mastery metrics. Another aspect includes assigning a work item corresponding to the first software component to the first developer based on the developer tier.

    DISTRIBUTION OF USER SPECIFIC DATA ELEMENTS IN A REPLICATION ENVIRONMENT

    公开(公告)号:US20210383006A1

    公开(公告)日:2021-12-09

    申请号:US16896289

    申请日:2020-06-09

    Abstract: Aspects include receiving a notification that a value of a data element stored in a source storage location in a source format has been changed to an updated value. The change is replicated to a plurality of target storage locations. The replicating includes, for each of the plurality of target storage locations, determining a target format of the data element in the target storage location. The target format is one of a plurality of different formats, including the source format. Each of the different formats provide a different level of data protection for the data element. In response to determining that the target format is not the same as the source format, the updated value of the data element is converted into the target format, and the updated value of the data element is stored in the target format at the target storage location.

    Distribution of user specific data elements in a replication environment

    公开(公告)号:US11593498B2

    公开(公告)日:2023-02-28

    申请号:US16896289

    申请日:2020-06-09

    Abstract: Aspects include receiving a notification that a value of a data element stored in a source storage location in a source format has been changed to an updated value. The change is replicated to a plurality of target storage locations. The replicating includes, for each of the plurality of target storage locations, determining a target format of the data element in the target storage location. The target format is one of a plurality of different formats, including the source format. Each of the different formats provide a different level of data protection for the data element. In response to determining that the target format is not the same as the source format, the updated value of the data element is converted into the target format, and the updated value of the data element is stored in the target format at the target storage location.

    REINFORCEMENT LEARNING FOR TESTING SUITE GENERATION

    公开(公告)号:US20220188627A1

    公开(公告)日:2022-06-16

    申请号:US17121796

    申请日:2020-12-15

    Abstract: Aspects of the invention include mutating each neural network of a portion of a first array of neural networks, wherein each neural network of the first array of neural networks is configured to select a respective sequence of test cases for testing a computing infrastructure. Causing each neural network of a second array of neural networks to select a respective sequence of test cases for testing the computing infrastructure. Generating a child neural network by performing a crossover operation between a mutated neural network of the portion of the first array and a neural network of the second array of neural networks, the child neural network generating a new sequence of test cases for testing the computing infrastructure.

    PROBLEM RECORD MANAGEMENT USING EXPERTISE SCORE VECTOR

    公开(公告)号:US20210224719A1

    公开(公告)日:2021-07-22

    申请号:US16749019

    申请日:2020-01-22

    Abstract: Techniques for problem record management using an expertise score vector for software component management are described herein. An aspect includes receiving a problem record associated with a first work item of a software component, the first work item being associated with a first developer. Another aspect includes creating a second work item corresponding to the problem record. Another aspect includes assigning the second work item to a second developer. Another aspect includes determining that computer code from the second developer resolves the problem record. Another aspect includes, based on determining that the problem record is resolved, increasing an expertise score of the second developer.

    ADAPTIVE TF-IDF INFERENCE ENGINE
    8.
    发明申请

    公开(公告)号:US20240419704A1

    公开(公告)日:2024-12-19

    申请号:US18335478

    申请日:2023-06-15

    Abstract: In an approach, a processor preprocesses a corpus of documents of a given subject matter by: scanning each document in the corpus to identify stop words, which either is a high occurrence word that appears in at least a first pre-set threshold number of documents or a low occurrence word that appears in less than a second pre-set threshold number of documents; adding the stop words to a list of stop words; performing a spellcheck function on the corpus of documents; scanning each document in the corpus to identify subject matter relevant words based on the given subject matter; adding the identified SMR words to a list of SMR words; and assigning a weight to each identified SMR word based on a term frequency. A processor performs a similarity assessment on the corpus using the list of stop words and the list of SMR words with associated weights.

    DYNAMIC FORMATION OF MATERIAL HANDLING VEHICLE

    公开(公告)号:US20240269831A1

    公开(公告)日:2024-08-15

    申请号:US18169291

    申请日:2023-02-15

    CPC classification number: B25J9/1617

    Abstract: A computer system, computer readable storage medium, and computer-implemented method for operating a plurality of material handling units in a unitary configuration. The method includes determining objects to be transported from first locations to second locations. The method also includes gathering, subject to the determining the one or more objects, information with respect to characteristics of the objects. The method further includes determining, subject to the gathering of information, characteristics of a unitary material transport vehicle to transport the objects from the first locations to the second locations. The method also includes determining, subject to the determining the characteristics of the unitary material transport vehicle, a number of material handling units to form the unitary material transport vehicle. The method further includes assembling the unitary material transport vehicle. The unitary material transport vehicle includes the plurality of material handling units assembled into a unitary configuration.

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