بدائل البحث:
iterative optimization » objective optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
based iterative » based integrative (توسيع البحث), based generative (توسيع البحث), based alternatives (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary best » binary depot (توسيع البحث)
best based » test based (توسيع البحث), bert based (توسيع البحث), tests based (توسيع البحث)
iterative optimization » objective optimization (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
based iterative » based integrative (توسيع البحث), based generative (توسيع البحث), based alternatives (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary best » binary depot (توسيع البحث)
best based » test based (توسيع البحث), bert based (توسيع البحث), tests based (توسيع البحث)
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41
Parameter setting for LSTM.
منشور في 2023"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
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42
LITNET-2020 data splitting approach.
منشور في 2023"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
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43
Transformation of symbolic features in NSL-KDD.
منشور في 2023"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
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44
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45
DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"
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46
Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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47
Models and Dataset
منشور في 2025"…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …"
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48
Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx
منشور في 2020"…In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. …"
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49
Supplementary Material 8
منشور في 2025"…</li><li><b>Adaboost: </b>A boosting algorithm that combines weak classifiers iteratively, refining predictions and improving the identification of antimicrobial resistance patterns.…"
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50
Seed mix selection model
منشور في 2022"…For each data set, we initialized a starting population of plant species equal to the desired number of plant species in the mix. The genetic algorithm then operated over 1000 iterations, applying crossover and mutation processes to optimize bee richness. …"