Search alternatives:
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
work optimization » wolf optimization (Expand Search), swarm optimization (Expand Search), dose optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary rate » binary data (Expand Search), binary image (Expand Search)
based work » based network (Expand Search)
rate from » rates from (Expand Search)
from optimization » fox optimization (Expand Search), swarm optimization (Expand Search), codon optimization (Expand Search)
work optimization » wolf optimization (Expand Search), swarm optimization (Expand Search), dose optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
binary rate » binary data (Expand Search), binary image (Expand Search)
based work » based network (Expand Search)
rate from » rates from (Expand Search)
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MSE for ILSTM algorithm in binary classification.
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. …”
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DataSheet1_Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization.pdf
Published 2024“…<p>Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. …”
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DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf
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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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…The binary GWO algorithm identifies the most relevant features from </p><p dir="ltr">dermatological images, eliminating redundancy and reducing the computational burden. …”
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…Future work aims to generalize this algorithm for broader biological applications by training additional Cellpose models and adapting the A* framework.…”
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Classification baseline performance.
Published 2025“…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …”
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Feature selection results.
Published 2025“…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …”
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ANOVA test result.
Published 2025“…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …”
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Summary of literature review.
Published 2025“…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …”
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Contextual Dynamic Pricing with Strategic Buyers
Published 2024“…We then establish an <math><mrow><mi>O</mi><mo>(</mo><msqrt><mi>T</mi></msqrt><mo>)</mo></mrow></math> regret upper bound of our proposed policy and an <math><mrow><mi>Ω</mi><mo>(</mo><msqrt><mi>T</mi></msqrt><mo>)</mo></mrow></math> regret lower bound for any pricing policy within our problem setting. This underscores the rate optimality of our policy. Importantly, our policy is not a mere amalgamation of existing dynamic pricing policies and strategic behavior handling algorithms. …”
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
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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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”