Parallel scatter search algorithms for exam timetabling. (c2009) by Haidar, Ghia Abdullah Sleiman

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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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Fuzzy simulated evolution algorithm for multi-objectiveoptimization of VLSI placement by Sait, Sadiq M.

“…A fuzzy simulated evolution algorithm is presented for multi-objective minimization of VLSI cell placement problem. …”
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Pre-training on Multi-modal for Improved Persona Detection Using Multi Datasets by Abdulla, Salwa

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A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

“…The percentage of improvement is more than 75% over the best known practical algorithm for the worst case. …”

Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier by Yassine Himeur (14158821)

“…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …”

Using artificial intelligence to improve body iron quantification: A scoping review by Abdulqadir J. Nashwan (11659453)

Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

“…The local search operator employs a single insertion approach, while the acceptance–rejection criteria are based on a constant temperature. Parameters of both ES and IG algorithms are calibrated using the Multifactor analysis of variance technique. …”

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

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. New approaches are needed to enhance the existing techniques, both to reduce execution time and improve fault coverage. …”
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

“…This class of ILC algorithms have been proposed aiming at improving the learning efficiency and performance. …”
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…The best thresholding values are found using various techniques, including Otsu and Kapur-based techniques. These techniques work well for bi-level thresholding, but when used to find the appropriate thresholds for multi-level thresholding, there will be issues with long calculation times, high computational costs, and the need for accuracy improvements. …”
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I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams by Raun, Kristo

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

“…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. The proposed framework is extendable and configurable by adding algorithms supported by the CARET package implemented in the R programming language. …”

Prediction of Multiple Clinical Complications in Cancer Patients to Ensure Hospital Preparedness and Improved Cancer Care by Regina Padmanabhan (14231606)

“…<p dir="ltr">Reliable and rapid medical diagnosis is the cornerstone for improving the survival rate and quality of life of cancer patients. …”

New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

“…A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. The eZDSP-F28335 platform has been used for practical implementation and results validation of the proposed technique. …”

A new family of multi-step quasi-Newton algorithms for unconstrained optimization by Obeid, Samir

“…One member of the family is tested against earlier developed algorithms of the multi-step type. Performance improvement is evident in our presented results, thus verifying the importance of the minimum curvature framework…”
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A new tabu search algorithm for the long-term hydro scheduling problem by Mantawy, A.H.

“…The algorithm is based on using the short-term memory of the tabu search (TS) approach to solve the nonlinear optimization problem in continuous variables of the LTHSP. …”
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