Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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A Tabu Search algorithm for mapping data to multicomputers. (c1997) by Diab, Kamal M.

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Allocating data to distributed-memory multiprocessors by genetic algorithms by Mansour, Nashat

“…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors by 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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Parallel physical optimization algorithms for allocating data to multicomputer nodes by Mansour, Nashat

“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

Subjects: “…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…”
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”

Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

“…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …”
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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

Subjects: “…Cluster analysis -- Data processing…”
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Fault-Tolerant Network Topologies for Datacenters by Attia, Heba Mahmoud Helal

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GenDE: A CRF-Based Data Extractor by Kayed, Mohammed

“…The experiments show an encouraging result as it outperforms the CSP-based extractor algorithm (95% and 96% of recall and precision, respectively). …”
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On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

The automation of the development of classification models and improvement of model quality using feature engineering techniques by 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. …”

Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …”

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

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Correlation Clustering with Overlaps by Fakhereldine, Amin

“…Moreover, we allow the new vertex splitting operation, which allows the resulting clusters to overlap. In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The results show that the Random forest model performed better in terms of accuracy of 90.12% as compared to other models. …”
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