بدائل البحث:
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), process optimization (توسيع البحث)
dose optimization » based optimization (توسيع البحث), model optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based driven » based diet (توسيع البحث), wave driven (توسيع البحث), user driven (توسيع البحث)
driven optimization » design optimization (توسيع البحث), guided optimization (توسيع البحث), process optimization (توسيع البحث)
dose optimization » based optimization (توسيع البحث), model optimization (توسيع البحث), wolf optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
based driven » based diet (توسيع البحث), wave driven (توسيع البحث), user driven (توسيع البحث)
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 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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2
the functioning of BRPSO.
منشور في 2025"…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
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3
Characteristic of 6- and 10-story SMRF [99,98].
منشور في 2025"…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
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4
The RFD’s behavior mechanism (2002).
منشور في 2025"…A sensitivity analysis of key RFD parameters, including frictional moment and rigid beam length, highlights their influence on seismic performance. The optimization problem is formulated based on the seismic energy dissipation concept, employing a modified binary and real-coded particle swarm optimization (BRPSO) algorithm. …"
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5
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Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"