بدائل البحث:
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
element » elements (توسيع البحث)
search » research (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
element » elements (توسيع البحث)
search » research (توسيع البحث)
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121
A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
منشور في 2025"…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …"
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122
Predicting Plasma Vitamin C Using Machine Learning
منشور في 2022"…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …"
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123
Stochastic Search Algorithms for Exam Scheduling
منشور في 2007"…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …"
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124
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125
Robust Control Of Sampled Data Systems
منشور في 2020"…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…"
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article -
126
Robust Control Of Sampled Data Systems
منشور في 2020"…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…"
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article -
127
Robust Control Of Sampled Data Systems
منشور في 2020"…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…"
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article -
128
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
منشور في 2024"…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …"
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129
Oversampling techniques for imbalanced data in regression
منشور في 2024"…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …"
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130
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131
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
منشور في 2022"…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …"
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132
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
منشور في 2024"…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …"
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133
Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence
منشور في 2020"…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …"
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134
Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
منشور في 2023"…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …"
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135
Data Redundancy Management in Connected Environments
منشور في 2020"…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …"
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conferenceObject -
136
Unsupervised outlier detection in multidimensional data
منشور في 2022"…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …"
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137
Android Malware Detection Using Machine Learning
منشور في 2024"…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …"
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138
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
منشور في 2023"…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …"
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139
Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
منشور في 2022"…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"
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140
Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
منشور في 2023"…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …"