Showing 1 - 20 results of 22 for search '(( binary scale models optimization algorithm ) OR ( binary base robust estimation algorithm ))', query time: 0.57s Refine Results
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    Determination of the Solute Content and Volumetric Properties of Binary Ionic Liquid Mixtures Using a Global Regularity of Molar Volume Expansion by Javad Hekayati (1383249)

    Published 2021
    “…For instance, the water content, which is of great significance in IL studies, can easily be estimated using the proposed algorithm. By doing so, an overall AARD of 3.47% was obtained for the estimation of the water content of 68 binary systems. …”
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    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
    “…The solubility predictions of fusidic acid, fusidic acid acetone solvate, and sodium fusidate in various single solvents show good agreement with experimental solubility with average squared relative errors of 0.055, 0.079, and 0.084 in logarithmic mole fraction scale, respectively. The model moreover predicts solubilities in binary solvent mixture and as a function of temperature in satisfactory agreement with experimental solubility.…”
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    Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data by Fei Xue (24567)

    Published 2021
    “…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”
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    QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm by Z.Y. Algamal (5547620)

    Published 2020
    “…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …”
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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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    Table 1_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... by Lucas L. Shilugu (22644302)

    Published 2025
    “…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …”
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    Table 2_Provider fidelity in tuberculosis screening practices among adolescents and adults living with HIV in public health facilities in Tanzania: a cross-sectional evaluation.doc... by Lucas L. Shilugu (22644302)

    Published 2025
    “…Modified Poisson regression with robust variance was used to estimate prevalence ratios (PRs) to determine factors associated with two binary outcomes: (1) consistent TB screening over 12-month period, and (2) correct utilization of the screening tool. …”
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    An AI-based Ecosystem for Real-time Gravitational Wave Analyses by Erik Katsavounidis (19369348)

    Published 2024
    “…These searches include A-frame, a low-latency machine learning pipeline for compact binary sources of gravitational waves, DeepClean, a deep learning-based denoising scheme for astrophysical gravitational waves, GWAK, a semi-supervised AI strategy to identify unmodeled gravitational wave transients, and AMPLFI, a pipeline for deep learning-based parameter estimation, leading to latency improvements for multi-messenger targets. …”