Three-phase approach for curriculum-based course timetabling problem. (c2012) by Jazzar, Hanaa Salem El-

Get full text
Get full text

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …”

A decentralized load balancing strategy for parallel search-three optimization. (c2010) by Mouawad, Amer E.

Get full text
Get full text

Three-phase simulated annealing algorithms for exam scheduling by Mansour, Nashat

“…Hence, we refer to our solution methods as 3-phase simulated annealing (3PSA). We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. …”
Get full text
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Data reductions and combinatorial bounds for improved approximation algorithms by Abu-Khzam, Faisal N.

Get full text
Get full text
Get full text
Get full text

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

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. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…The proposed algorithm has been tested on three tank system pilot plant and Ain El Kebira Cement rotary kiln process. …”

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. …”
Get full text
Get full text
Get full text

A comparison of data mapping algorithms for parallel iterative PDE solvers by Mansour, Nashat

Get full text
Get full text
Get full text

Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations by Mansour, Nashat

“…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. …”
Get full text
Get full text
Get full text

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

Get full text
Get full text
Get full text

Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples by unknown

Get full text
Get full text

How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)

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. …”

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. …”

A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…Additionally, it was able to identify several differentiable regions in the real data set and on different chromosomes. However, we noticed that chromosomes 1, 3 and 6 had the highest occurrence rate of differentiable motifs (9, 8 and 6 motifs respectively). …”
Get full text
Get full text

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

Get full text
Get full text