Parallel physical optimization algorithms for allocating data to multicomputer nodes حسب Mansour, Nashat

"…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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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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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models حسب Asan G. A. Muthalif (16888818)

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

"…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. …"

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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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

"…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
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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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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique حسب J. Jayapradha (21323774)

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion حسب PKA Chitra (21749216)

"…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …"

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System حسب Ameema Zainab (16864263)

الموضوعات:

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

A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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Genetic and heuristic algorithms for regrouping service sites. (c2000) حسب Tabbara, Hiba

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Graph Computing Systems and Partitioning Techniques: A Survey حسب Tewodros Alemu Ayall (19273717)

الموضوعات:

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting حسب Mohamed Massaoudi (16888710)

الموضوعات:

Second-order conic programming for data envelopment analysis models حسب Mourad, Nahia

"…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …"
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Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms حسب ALSHEHHI, OMAR KHALID HAMAD

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The automation of the development of classification models and improvement of model quality using feature engineering techniques حسب Sjoerd Boeschoten (17347045)

"…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …"

Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks حسب Kalash, Saeddin

"…Moreover, the collection of all data may lead to collect data representing redundant information which may reduce the network efficiency. …"
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