Showing 121 - 140 results of 192 for search '(( binary a model optimization algorithm ) OR ( binary based robust optimization algorithm ))*', query time: 0.48s Refine Results
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    A new fast filtering algorithm for a 3D point cloud based on RGB-D information by Chaochuan Jia (7256237)

    Published 2019
    “…This method aligns the color image to the depth image, and the color mapping image is converted to an HSV image. Then, the optimal segmentation threshold of the V image that is calculated by using the Otsu algorithm is applied to segment the color mapping image into a binary image, which is used to extract the valid point cloud from the original point cloud with outliers. …”
  5. 125

    Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model by Getachew S. Molla (6416744)

    Published 2019
    “…A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. …”
  6. 126

    Summary of existing CNN models. by Nicodemus Songose Awarayi (18414494)

    Published 2024
    “…The model was trained and evaluated using a 10-fold cross-validation sampling approach with a learning rate of 0.001 and 200 training epochs at each instance. …”
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    DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf by Marcel Dahms (9160118)

    Published 2022
    “…Improvement of the classification rate is expected with optimized model parameters and algorithms as well as with a larger spectral data base for training.…”
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    MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

    Published 2025
    “…<p dir="ltr">Geospatial optimization problems are fundamental research issues in geographic information science modeling, characterized by high dimensionality, dynamics, and discreteness. …”
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    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

    Published 2019
    “…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”
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    Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

    Published 2023
    “…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. There is a binary integer programming model for this problem in the literature, from which its authors proposed a genetic algorithm to obtain approximate solutions. …”
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    Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles by Peter S. Rice (11805875)

    Published 2025
    “…For this purpose, we have developed a general procedure that we use to model an experimentally relevant 270-atom Fe<sub>182</sub>C<sub>88</sub> NP using the neural network-assisted stochastic surface walk global optimization algorithm (SSW-NN). …”
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    Generalized Tensor Decomposition With Features on Multiple Modes by Jiaxin Hu (1327875)

    Published 2021
    “…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …”
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    Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx by Yupeng Li (507508)

    Published 2023
    “…</p>Methods<p>This paper establishes a medical prediction model for the first time on the basis of the enhanced particle swarm optimization (SRWPSO) algorithm and the fuzzy K-nearest neighbor (FKNN), called bSRWPSO-FKNN, which is practiced on a dataset related to patients with AD. …”
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    Summary of LITNET-2020 dataset. by Asmaa Ahmed Awad (16726315)

    Published 2023
    “…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”