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. …”

Integrated economic and environmental models for a multi stage cold supply chain under carbon tax regulation by Hariga, Moncer

“…The structural properties for the optimal solution of the three models are identified and solution algorithms are also proposed. …”
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Scheduling IoT Requests to Minimize Latency in Fog Computing by Alikarar, Mazin Abdelbadea Nasralla

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Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT by Arumugam K (18456690)

“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. In FT-Block (Federated transfer learning blockchain), several blockchains are applied to preserve privacy and security for all types of industrial applications. …”

A Survey of Data Clustering Techniques by Sobeh, Salma

“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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Improved Adaptive Backoff Algorithm for Optimal Channel Utilization in Large-Scale IEEE 802.15.4-Based Wireless Body Area Networks by El-Abd, Mohammed

“…In a previous work, we proposed the adaptive backoff algorithm (ABA), which adapts the contention window’s size to the value of the probability of collision, thus relating the contention resolution to the size of the WSN in an indirect manner. …”
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Improved Adaptive Backoff Algorithm for Optimal Channel Utilization in Large-Scale IEEE 802.15.4-Based Wireless Body Area Networks by El-Abd, Mohammed

“…In a previous work, we proposed the adaptive backoff algorithm (ABA), which adapts the contention window’s size to the value of the probability of collision, thus relating the contention resolution to the size of the WSN in an indirect manner. …”
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A Modified PWM Strategy With an Improved ANN Based MPPT Algorithm for Solar PV Fed NPC Inverter Driven Induction Motor Drives by Nazmul Islam Nahin (17949158)

“…Apart from that, a robust artificial neutral network (ANN) based incremental conductance maximum power point tracking (MPPT) algorithm is also introduced to control the dc-link voltage of the PV fed NPC inverter driven IMD system. …”

Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

“…In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”

A Graph Heuristic Approach for the Data Path Allocation Problem by Makhoul, Racha

“…The results show that the algorithm performs well while generating sub-optimal solutions.…”
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On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…</p><h3 dir="ltr">Results</h3><p dir="ltr">In the first example, all algorithms achieved similar optimal solutions in the two optimization scenarios, with differences arising primarily in computational efficiency. …”

PERF solutions for distributed query optimization. (c1999) by Fany, Roula

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Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

“…We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. …”

Collision-Free Autonomous Navigation Solution for Mobile Wheeled by Elsergany, Ahmed Moataz Mahmoud

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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”

Multi-Objective Task Allocation Via Multi-Agent Coalition Formation by Amer, Noha Tarek

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A clustering metaheuristic for large orienteering problems by Almiqdad Elzein (13141038)

“…The metaheuristic aims to dramatically improve the computation time of a given Orienteering Problem algorithm without a significant decrease in the solution quality of that algorithm, especially for large Orienteering Problems. …”

Mixed precision iterative refinement with adaptive precision sparse approximate inverse preconditioning by Noaman Khan (19810050)

“…<p dir="ltr">Hardware trends have motivated the development of mixed precision algorithms in numerical linear algebra, which aim to decrease runtime while maintaining acceptable accuracy. …”

Correlation Clustering via s-Club Cluster Edge Deletion by Makarem, Norma

“…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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