بدائل البحث:
based optimization » whale optimization (توسيع البحث)
binary wave » binary image (توسيع البحث)
wave based » made based (توسيع البحث), game based (توسيع البحث), rate based (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a based » ai based (توسيع البحث), _ based (توسيع البحث), 1 based (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary wave » binary image (توسيع البحث)
wave based » made based (توسيع البحث), game based (توسيع البحث), rate based (توسيع البحث)
binary a » binary _ (توسيع البحث), binary b (توسيع البحث), hilary a (توسيع البحث)
a based » ai based (توسيع البحث), _ based (توسيع البحث), 1 based (توسيع البحث)
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161
Transformation of symbolic features in NSL-KDD.
منشور في 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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162
datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf
منشور في 2021"…We introduce a graph neural network architecture for solving such optimization problems. …"
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163
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164
Contextual Dynamic Pricing with Strategic Buyers
منشور في 2024"…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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165
Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
منشور في 2025"…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …"
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166
Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
منشور في 2025"…The single predictor variable was the mushroom habitat, a categorical feature that was preprocessed using the One-Hot Encoding technique, resulting in seven distinct binary variables. …"
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167
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168
Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
منشور في 2020"…The proposed multilabel approaches convert the original 8-class problem into a set of three binary problems to facilitate the use of the CSP algorithm. …"
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169
Table_1_Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique.DOCX
منشور في 2023"…In the model, promotor sequences were encoded by three different kinds of feature descriptors, namely, accumulated nucleotide frequency, k-mer nucleotide composition, and binary encodings. The obtained features were optimized by using correlation and the mRMR-based algorithm. …"
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170
GSE96058 information.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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171
The performance of classifiers.
منشور في 2024"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"
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172
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173
Bayesian sequential design for sensitivity experiments with hybrid responses
منشور في 2023"…<p>In experimental design, a common problem seen in practice is when the result includes one binary response and multiple continuous responses. …"
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174
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease
منشور في 2025"…<i>Z</i> score standardization and independent sample <i>t</i> test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. …"
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175
Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP
منشور في 2021"…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …"
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176
DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…</p>Conclusions<p>Multi-parametric MRI-based radiomics combining with machine learning approaches provide a promising method to predict the molecular subtype and AR expression of breast cancer non-invasively.…"
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177
Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx
منشور في 2025"…To address these limitations, this study proposed a method for detecting litchi maturity states based on UAV remote sensing and YOLOv8-FPDW. …"
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178
Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…In e), the image is skeletonized by creating a line along the center of the lower jaw. Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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179
Sample image for illustration.
منشور في 2024"…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"
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180
Comparison analysis of computation time.
منشور في 2024"…This article introduces a Convex Based Feature Descriptor (CBFD) system designed to withstand rotation, lighting, and blur variations while remaining computationally efficient. …"