Properties of simulated annealing and genetic algorithms for mapping data to multicomputers حسب Mansour, Nashat

"…Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. …"
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

"…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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General applicability of genetic and simulated annealing algorithms for data mapping حسب Mansour, Nashat

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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection حسب Alok Singh Chauhan (8264985)

Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects حسب Majdi Mansouri (16869885)

"…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …"

Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) حسب Kawash, Jalal Y.

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Smart transportation solutions for faster emergency medical services response using an enhanced whale optimization algorithm حسب Hina Gupta (21842246)

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms حسب Arafat Rahman (8065562)

Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review حسب Francisco Monteiro-Guerra (16864122)

A comparison of data mapping algorithms for parallel iterative PDE solvers حسب Mansour, Nashat

"…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …"
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An enhanced k-means clustering algorithm for pattern discovery in healthcare data حسب Haraty, Ramzi A.

"…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …"
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

"…The primary tool used in the data supply chain is data batch processing which requires efficient scheduling. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach حسب Muhammad Adeel Asghar (6724982)

"…This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals. …"

Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality حسب KARAM, ZAINAB HAMDAN

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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models حسب Asan G. A. Muthalif (16888818)

Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization حسب Yassine Himeur (14158821)

"…However, they might not perform as expected, take much time in training, or not have enough input data to generalize well. To that end, deep transfer learning (DTL) and deep domain adaptation (DDA) have recently been proposed as promising solutions to alleviate these issues. …"

Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks حسب S. N. V. Bramareswara Rao (21768302)

"…Due to their reliance on sizable fault currents, classic fault detection techniques are no longer suitable for microgrids that employ inverter-interfaced distributed generation. Nowadays, deep learning algorithms are essential for ensuring the reliable, safe, and efficient operation of these complex energy systems. …"