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

“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing by Al Sadawi, Alia

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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain by Al Sadawi, Alia

“…The algorithm proved its effectiveness by allocating tasks with higher priority and weight while taking into consideration customers’ Service Level Agreement, time, and different types of costs, which led to a lower total cost of the batching process. …”
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Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

“…In certain situations, the requirement for clusters to be cliques was deemed excessively stringent, leading to the proposal of alternative relaxed clique models for dense subgraphs, such as s-club. In this work, we implement three approaches to tackle the 2-club clustering via edge deletion: a heuristic approach based on the influence of the edge to resolve maximum conflicts, a parameterized algorithm in which by deleting a maximum of k edges, the graph can be transformed into a 2-club cluster based on a branching algorithm, and the approach in Integer Linear Programming to find the optimized solution in an integer formulation. …”
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On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

“…Two new (linear) mathematical programming models are proposed for MOSWIPT. Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”

A Study on Applying Data Mining in Airline Industry for Demand Forecasting by predicting Item Criticality by KARAM, ZAINAB HAMDAN

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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

“…Findings Production, import, export, road construction and price are considered as the input data used in the present study. …”
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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. …”

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

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

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A genetic algorithm for corrective retesting. (c1995) by Fakih, Khaled A.

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

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

A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

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A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

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