Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

“…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”

Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

“…First, the OSF is detected and localized based on the grid current dynamics, where each switch fault generates a specific pattern in the current dynamics. OSF is tolerated by changing the switching function based on the location of the fault. …”

Enhanced Microgrid Reliability Through Optimal Battery Energy Storage System Type and Sizing by Mohammadreza Gholami (17032317)

“…To determine the optimized size, a firefly optimization algorithm is used as an efficient meta-heuristic approach. …”

Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…</p><h2>Other Information</h2> <p> Published in: Expert Systems with Applications<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.eswa.2024.124118" target="_blank">https://dx.doi.org/10.1016/j.eswa.2024.124118</a></p>…”

Prediction of biogas production from chemically treated co-digested agricultural waste using artificial neural network by Fares Almomani (12585685)

“…The developed model can be used to forecast the CMP as a function of operating temperature, the substrate composition, and chemical dose, and can be used for scaling-up and cost analysis purposes.…”

Improving the Resilience of Smart Distribution Networks against Cyber Attacks by ElYamani, Mohamed ElHusseiny Mohamed

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

“…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. …”

Critical exponents from the weak-coupling, strong-coupling and large-order parametrization of the hypergeometric (k+1Fk) approximants by Abouzeid M. Shalaby (16810695)

“…<p dir="ltr">In this work, we suggest a new parametrization for the hypergeometric (k+1Fk) approximants introduced by Mera et al. (2015). …”

Detecting protein complexes in protein interaction networks using Mapper and Graph Convolution Networks by Daou, Leonardo

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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. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…The performance of our approach is gauged against the traditional multi-label Naïve Bayes (MLNB) algorithm and is quantified through a suite of evaluation metrics. …”

Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…A cumulative updating loss function was employed for overall optimization, demonstrating remarkable superiority over traditional optimization techniques. …”

Deadline-based connection setup in wavelength-routed WDM networks by Fawaz, Wissam

“…Performance of this novel scheme is analyzed by accurately calculating various parameters, such as the fraction of connections provisioned on-time (i.e. prior to deadline expiration) and the average time it takes to successfully setup a connection. …”
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh (22565837)

“…Through systematic eigenvalue analysis and parameter sensitivity studies, complemented by time-domain verification in MATLAB/SIMULINK, we demonstrate the decisive influence of VSG control parameters on low-frequency oscillation (LFO) damping characteristics, transient frequency stability metrics, including the rate of change of frequency (ROCOF), maximum frequency deviation (<i>fnadir</i>), overshoot, and settling time. We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”

Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik Rafikiran (15838929)

“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AASP&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”

Regression testing web services-based applications by Tarhini, Abbas

“…Our algorithm selects every test sequence that corresponds to a different behavior in the modified system. …”
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Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems by Shaik, Rafikiran

“…The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. …”
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Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side by Ali Sharida (17947847)

“…Unlike MPC, IMPC offers a significantly reduced computational burden by omitting the iterative computations of the cost functions and states predictions. …”

Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

“…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. …”
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