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

“…These are a sequential hybrid GA, a coarse-grain GA and a fine-grain GA. The last two are based on models of natural evolution that are suitable for parallel implementation; they have been implemented on a hypercube and a Connection Machine. …”
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements by Stefano Nardean (14151900)

“…This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. …”

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

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Metaheuristic algorithms have also been presented in four primary behavior-based categories, i.e., evolutionary-based, swarm-intelligence-based, physics-based, and human-based, even though some literature works presented more categorization. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…A parallel simulator, based on PVM, was implemented for the proposed algorithm on a Linux Cluster. …”
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A Tabu Search Algorithm For Maintenance Scheduling Of Generating Units by El-Amin, I.

“…A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (MS) of electric generation units. …”
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A Tabu Search Algorithm For Maintenance Scheduling Of Generating Units by Duffuaa, S. O.

“…A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (MS) of electric generation units. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…Hundreds of such labeled graphs were used to train the model to predict the location of centroids. The objective is to produce a model capable of predicting centroids with greater accuracy than the traditional random initialization used in K-means. …”
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Parallel physical optimization algorithms for allocating data to multicomputer nodes by Mansour, Nashat

“…The parallel genetic algorithm (PGA) is based on a natural model of evolution. …”
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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

“…PGA has excellent speed-ups by virtue of the natural evolution model on which it is based. PSA and PNN include communication schemes adapted to the properties of the mapping problem and of the algorithms themselves for reducing the communication overhead. …”
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…The first is a comprehensive ML framework for the construction of diagnostic binary classification high accuracy models to predict T2DM in the United Arab Emirates based on STEPS style National Health Survey. …”
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Assessment of static pile design methods and non-linear analysis of pile driving by Abou-Jaoude, Grace G.

“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
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Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW) by Ayesha Maroof (17984053)

A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²), were used to assess the prediction accuracy of the models. The results of the correlation matrices showed that the blueberry yield and losses (leaf loss, blower loss) had medium to strong correlations accessed based on the correlation coefficient (r) range 0.37–0.79. …”