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

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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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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

“…We also present a technique for efficient mapping of large data sets. 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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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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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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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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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …”

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. …”

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

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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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Second-order conic programming for data envelopment analysis models by 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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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…The key features of modern power systems include the following: decreased total inertia caused by integration of renewable sources energy, stricter requirements for emergency control accuracy, highly digitized operation and control of power systems, and high volumes of data that describe power system operation. …”
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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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