Recent advances on artificial intelligence and learning techniques in cognitive radio networks by Abbas, Nadine

“…The literature survey is organized based on different artificial intelligence techniques such as fuzzy logic, genetic algorithms, neural networks, game theory, reinforcement learning, support vector machine, case-based reasoning, entropy, Bayesian, Markov model, multi-agent systems, and artificial bee colony algorithm. …”
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Design of a vibration absorber for harmonically forced damped systems by Issa, Jimmy

“…For a given damping ratio of the primary system and mass ratio of the system, the optimal stiffness and damping ratios of the absorber are calculated numerically. Two different numerical approaches are used in solving the problem; the first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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Direct sensitivity analysis of nonlinear distortion in RF circuits using multidimensional moments by Tannir, Dani

“…We show that the sensitivities of key distortion figures of merit, including the 1 dB compression point and different intercept points, at all outputs in the circuit can be obtained with minimal additional computation cost to that of the original algorithm, thereby providing insight into the circuit performance.…”
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Thermal convection of fluid in fractured media by Sfeir, Abdallah

“…Including this phenomenon in a modelling process led us to propose a development of the UDEC code. The computational algorithm is based on the differences between the rates of convective and conductive heat transfers. …”
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Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends by Abdellatif M. Sadeq (16931841)

“…In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. …”

Reinforcement R-learning model for time scheduling of on-demand fog placement by Farhat, Peter

“…Therefore, there is a need for an intelligent model capable of scheduling fog placement based on the user’s requests. In this paper, we propose a Fog Scheduling Decision model based on reinforcement R-learning, which focuses on studying the behavior of service requesters and produces a suitable fog placement schedule based on the concept of average reward. …”
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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. …”

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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A modified optimal design of a vibration absorber for ground motion isolation by Issa, Jimmy S.

“…This approximate analytical solution is validated through comparison with the exact optimal parameters which were calculated numerically using two different numerical optimization methods. The first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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A novel on design and implementation of hybrid MPPT controllers for solar PV systems under various partial shading conditions by Chakarajamula Hussaian Basha (21633167)

“…In this work, various hybrid optimization controllers are studied for tracing the working power point of the PV under different Partial Shading Conditions. The studied hybrid optimization MPPT methods are equated in terms of oscillations across MPP, output power extraction, settling time of the MPP, dependency on the PV modeling, operating duty value of the converter, error finding accuracy of MPPT, algorithm complexity, tracking speed, periodic tuning required, and the number of sensing parameters utilized. …”

Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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Mining airline data for CRM strategies. (c2006) by Maalouf, Lena

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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”

An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control by Mahmoud Dahmani (18810247)

“…The first three techniques were automatic, employ correlation, and were variants of template matching, whereas the last one uses convolutional neural networks (CNNs). Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. …”

SPA & MLST typing as epidemiological tools for the study of MRSA & MSSA Isolates in Lebanon. (c2009) by Rizk, Mazen

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Portable Electromagnetic Surface Profiling System by Al Homssi, Bassel Mohamad

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Low Cost Autopilot Design Using Fuzzy Supervisory Control by Hadi, Mahmoud

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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. …”

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. …”

Random vector functional link network: Recent developments, applications, and future directions by A.K. Malik (16003193)

“…To overcome these issues, randomization based neural networks such as random vector functional link (RVFL) network have been proposed. …”