A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading by Saoud A. Al-Janahi (18877213)

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

Framework for rapid design and optimisation of immersive battery cooling system by Ali Almshahy (23544823)

“…The CFD model of a battery module is developed to train an ultra-fast metamodel for battery geometry optimisation. Two key parameters are optimised, namely: battery gap spacing (3–10 mm) and inlet/outlet width (5–15 mm), via Optimal Latin Hypercube Sampling, Support Vector Regression, and GDE3 algorithm. …”

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

“…These retransmissions further enhance the delay in LoRa networks. This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”

Optimisation of PV Cleaning Practices: Comparison Between Performance Based and Periodic Based Approaches by ALHAJERI, RASHED ABDULLA

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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…Thus, models have the potential to optimise patient care through dynamic adjustments.</p><h3>Conclusion</h3><p dir="ltr">The application of ML models in optimising patient–nurse assignments presents significant opportunities for improving healthcare delivery. …”

Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach by S. Punitha (17945654)

Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls by SANAD, AYMAN ADEL AHMED

“…Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. …”
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An Optimal Energy Dispatch Management System for Hybrid Power Plants: PV-Grid-Battery-Diesel Generator-Pumped Hydro Storage by Fatma Ahmed (11084787)

Robust design of multimachine power system stabilisers using tabusearch algorithm by Abido, M.A.

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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”

A Closed Queueing Networks Approach for an Optimal Heterogeneous Fleet Size of an Inter-Facility Bulk Material Transfer System by Mohamed Amjath (17542512)

“…Conclusions: These findings affirm the presented analytical approach’s robustness in optimising interfacility material transfer operations with heterogeneous truck fleets, demonstrating real-world applications.…”

Unit commitment by tabu search by Mantawy, A.H.

“…An application of the tabu search (TS) method to solve the unit commitment problem (UCP) is presented. …”
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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…In general, such problems in design optimisation or virtual reality applications must be solved repetitively in a short period using direct methods such as nonlinear finite element analysis. …”

Fleet sizing of trucks for an inter-facility material handling system using closed queueing networks by Mohamed Amjath (17542512)

“…Within this context, the problem is modelled as a closed queueing network (CQN) combined with mixed-integer nonlinear programming (MINLP) to determine the optimal fleet size. This study proposes an analytical method based on sequential quadratic programming (SQP) methodology coupled with a mean value analysis (MVA) algorithm to solve this NP-Hard problem. …”

Modélisation et validation des modèles de véhicules hybrides by Mansour, Charbel

“…Une stratégie de contrôle prédictive pour le GMP THS-II est également élaborée par programmation dynamique (DP), afin d'optimiser la consommation sur une route spécifiée au lieu d'une optimisation instantanée telle la stratégie RB, et d'accélérer le temps de calcul de l'algorithme DP pour faciliter son implémentation au sein du véhicule pour des applications temps réel. …”
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