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

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Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.…”
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

“…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …”

A neural networks algorithm for data path synthesis by 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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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique by J. Jayapradha (21323774)

Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices by Khawam, Yahya Bader

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

“…<p>The nonlinearity behaviour of magnetorheological fluid (MRF) can be described using a number of established models such as Bingham and Modified Bouc-Wen models. …”

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

DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data by 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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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”

Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by 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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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing by Al Sadawi, Alia

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Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

“…The algorithms include a parallel genetic algorithm (PGA), a parallel neural network algorithm (PNN) and a parallel simulated annealing algorithm (PSA). …”
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