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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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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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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …”
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…A major challenge in bioprocess simulation is the lack of physical and chemical property databases for biochemicals. A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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Image2_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf
Published 2023“…<p>We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. …”
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7
Datasets and their properties.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
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Parameter settings.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
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Image1_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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Image4_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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Image5_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.jpg
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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Image3_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.JPEG
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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13
DataSheet1_Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm.docx
Published 2022“…In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. …”
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Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
Published 2019“…The overall procedure automatically generates many unique minimum energy geometries of clusters with size from 2 up to n using this evolutionary growth strategy. …”
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17
Pressure-Stabilized Zinc Trifluoride
Published 2020“…By combining the particle swarm optimization algorithm with first-principles calculation, the high-pressure phase diagram of Zn–F binary compounds was established. …”
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18
SHAP bar plot.
Published 2025“…Participants were categorized into two groups: the CI group (n = 53) and the non-CI group (n = 362). …”
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19
Sample screening flowchart.
Published 2025“…Participants were categorized into two groups: the CI group (n = 53) and the non-CI group (n = 362). …”
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Descriptive statistics for variables.
Published 2025“…Participants were categorized into two groups: the CI group (n = 53) and the non-CI group (n = 362). …”