Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب 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. …"

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

"…We demonstrated the applicability of feature engineering techniques such as data imputation, transformation (e.g., scaling, centering, etc.), and data balancing using several case studies and the proposed semi-automated framework. …"

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

"…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …"

Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms حسب Tekli, Joe

"…Various weighting functions and intelligent search algorithms have been developed for that purpose and will be presented here. …"
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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems حسب Abu Zitar, Raed

"…Therefore, the paper discusses the development of the Lévy flight-based reptile search algorithm with local search capability and evaluates its potential against challenging power systems engineering optimization problems. …"
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Developing a UAE-Based Disputes Prediction Model using Machine Learning حسب Abu Laila, Ibrahim Wasef Subhi

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Social spider optimization algorithm: survey and new applications حسب Abualigah, Laith

"…This algorithm has been developed over time, resulting in many versions besides theories and findings. …"
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A genetic algorithm for testable data path synthesis حسب Harmanani, H.

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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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Data reductions and combinatorial bounds for improved approximation algorithms حسب Abu-Khzam, Faisal N.

"…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …"
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Distributed dimension reduction algorithms for widely dispersed data حسب Abu-Khzam, F.N.

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Optimizing Energy Consumption of Cloud Computing IaaS حسب Mohamed, Huda Ibrahim

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A comparative study of replacement algorithms used in the scalable asynchronous cache consistency scheme حسب Haraty, Ramzi A.

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

Data damage assessment and recovery algorithm from malicious attacks in healthcare data sharing systems حسب Haraty, Ramzi A.

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Public health utility of cause of death data: applying empirical algorithms to improve data quality حسب Sarah Charlotte Johnson (9715415)

Estimating Construction Project Duration Using a Machine Learning Algorithm حسب Nasr, Joshua

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A Hash-Based Assessment and Recovery Algorithm for Distributed Healthcare Systems Using Blockchain Technology حسب Jaber, Mohammad

"…Numerous damage assessment and recovery algorithms have been proposed in the literature. In this work, we present a distributed algorithm that uses blockchain technology and hash tables to solve the information warfare problem in healthcare systems. …"
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A Scatter search algorithm for exam scheduling. (c2006) حسب Isahakian, Vatche Raffi

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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach حسب BILQUISE, GHAZALA

"…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …"
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