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learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
element » elements (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
element » elements (توسيع البحث)
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161
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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162
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163
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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164
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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165
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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166
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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167
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 -
168
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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169
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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170
Deep and transfer learning for building occupancy detection: A review and comparative analysis
منشور في 2022"…Occupancy data might be collected using a variety of devices. …"
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171
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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172
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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173
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175
Graph Contraction for Mapping Data on Parallel Computers
منشور في 1994"…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …"
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176
A kernelization algorithm for d-Hitting Set
منشور في 2010"…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …"
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177
Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
منشور في 2024"…In this context, Deep Reinforcement Learning (DRL) emerges as a technological advancement that improves the healthcare by enabling smart, adaptive, and real-time decision-making processes. …"
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178
Mapping realistic data sets on parallel computers
منشور في 1993"…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…"
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conferenceObject -
179
Parallel genetic algorithm for disease-gene association
منشور في 2011"…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…"
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conferenceObject -
180