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Showing 1 - 9 results of 9 for search '(( linear single based optimization algorithm ) OR ( binary data process optimization algorithm ))', query time: 0.10s Refine Results
  1. 1
    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm

    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

    Published 2023
    “…In this study, features were extracted from signals in time, frequency, and time–frequency domains. The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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  2. 2
    Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learning Models Based on Dimensionality Reduction

    Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

    Published 2020
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  3. 3
    VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems

    VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

    Published 2019
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  4. 4
    Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems

    Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial Systems by Tarek Berghout (16905132)

    Published 2021
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  5. 5
    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach

    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

    Published 2019
    “…<p dir="ltr">Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. …”
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  6. 6
    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques

    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
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  7. 7
    Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods

    Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

    Published 2022
    “…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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  8. 8
    A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns

    A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns by Md Ferdous Wahid (13485799)

    Published 2023
    “…The important feature subset is identified using the modified Binary Grey Wolf Optimization Particle Swarm Optimization (BGWOPSO) algorithm. …”
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  9. 9
    Uplink Noma in UAV-Assisted IoT Networks

    Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

    Published 2022
    “…Given the complexity of the problem and the incomplete knowledge about the environment, the problem is divided into two subproblems: the first models the UAV trajectory and the selection of the first device in the NOMA cluster at each time slot as a Markov Decision Process, and uses Proximal Policy Optimization to solve it. The second device is then selected using a heuristic algorithm based on prioritizing devices with higher bit rate requirements and strict deadlines. …”
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