Distributed dimension reduction algorithms for widely dispersed data by Abu-Khzam, F.N.

“…Stress function measurements indicate that the distributed algorithm is highly competitive with the original FastMap heuristic.…”
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An Evolutionary Algorithm for the Allocation Problem in High-Level Synthesis by Harmanani, Haidar

“…The method performs allocation of functional units, registers, and multiplexers in addition to controller synthesis with the objective of minimizing the cost of hardware resources. …”
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Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review by Yazeed Yasin Ghadi (16667109)

“…Moreover, this study also addresses issues of adapting machine learning algorithms to accommodate the sensors’ functionalities in the network configuration. …”

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

Subjects:

Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning by Sait, Sadiq M.

“…Fuzzy rules are used in order to design the overall multi-objective cost function that integrates the costs of three objectives in a single overall cost value. …”
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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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AGEomics Biomarkers and Machine Learning—Realizing the Potential of Protein Glycation in Clinical Diagnostics by Naila Rabbani (291722)

“…AGEomics biomarkers have been used in diagnostic algorithms using machine learning methods. In this review, I describe the utility of AGEomics biomarkers and provide evidence why these are close to the phenotype of a condition or disease compared to other metabolites and metabolomic approaches and how to train and test algorithms for clinical diagnostic and screening applications with high accuracy, sensitivity and specificity using machine learning approaches.…”

Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. …”
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Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…<h3>Background</h3><p dir="ltr">Existing BRCA2-specific variant pathogenicity prediction algorithms focus on the prediction of the functional impact of a subtype of variants alone. …”

Economic Production Lot-Sizing For An Unreliable Machine Under Imperfect Age-Based Maintenance Policy by El-Ferik, S

“…Numerical results are provided to illustrate both the use of the algorithm in the study of the optimal cost function and the latter's sensitivity to different changes in cost factors. …”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…The three heuristics are applied on the same optimization problem and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search frominitial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time (iteration count), and (4) the number of solutions found at successive intervals of the cost function. …”
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm by Zerguine, A.

“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…The fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

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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 solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems by Abu Zitar, Raed

“…This paper is a further attempt to offer a better optimizing structure, therefore, aims to provide a better-performing algorithm both for designing an appropriate proportional-integral-derivative (PID) controller to effectively operate an automatic voltage regulator (AVR) system and extracting the optimum parameters of a power system stabilizer (PSS) employed in a single-machine infinite-bus (SMIB) power system. …”
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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