Blood Glucose Regulation Modelling and Intelligent Control by Nasar, Nabeel

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Modeling of magnetization curves for computer-aided design by Abuelma’atti, M.T.

“…A simple algorithm is presented for obtaining the coefficients of the sine-series function for modelling the magnetization curves of magnetic materials. …”
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Wiener-Hammerstein Model Identification-Recursive lgorithms by Emara-Shabaik, Husam

“…Recursive algorithms for parameter estimation of Wiener-Hammerstein (W-H)models are developed. …”
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Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”

ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

“…The best solutions adopted in this situation are often based on optimization algorithms that generate the controller’s gains in each period where there is an internal or external perturbation, adapting the behaviors of the PID against the system’s nonlinearity. …”

A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…A multi-objective mixed-integer non-linear programming (MINLP) model is developed. To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”

Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

“…Exchange rate data from the Lebanese currency crisis period of 1985-1992 is used for training, testing and evaluation of the models. Forecasting performance measures represented by well established error functions are presented for the three models. …”
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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…This is achieved by predicting subsequent tokens, such as keywords, variable names, types, function names, operators, and more. Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”

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

“…Several approaches have been suggested to identify label-specific characteristics for creating distinct categorization models. Our proposed methodology seeks to encapsulate and systematically represent label correlations within the learning framework. …”

Particle swarm optimization approach for protein structure prediction in the 3D HP model by Mansour, Nashat

“…In this paper, we present a particle swarm optimization (PSO) based algorithm for predicting protein structures in the 3D hydrophobic polar model. …”
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Neural Networks as a Convex Problem by Khalil, Baha

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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. Nevertheless, both IMPC and MPC rely significantly on the dynamic model of the power converter. …”

Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…We trained the model on 80% of the expert reviewed variants by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium and tested its performance on the remaining 20%, as well as on an independent set of variants of uncertain significance with experimentally determined functional scores.…”

Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks by Zahidi, Sarah Hussain

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

“…The artificial neural network demonstrates a higher prediction accuracy and is used as the system model in the proposed control framework. 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. …”

H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling by Peixoto, Eduardo

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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

"A Tabu Search Approach for the Design of Variable Structure Load Frequency Controller Incorporating Model Nonlinearities" by Al-Hamouz, Z.

“…The designed VSC is applied to LFC model that incorporates the nonlinearity of the Generation Rate Constraint (GRC). …”
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A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems by Kandil, Sarah M.

“…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …”
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