Optimization of PV Cleaning Practices: Comparison Between Performance-Based and Periodic-Based Approaches by Abdulla Alhajeri, Rashed

“…Other findings of the study included higher tilt angles that resulted in lower cleaning requirements and thin-film PV panels that required less cleaning than first generation PV panels (mono/poly crystalline). The algorithm is an effective yet simple tool to help operators optimize the NCB of their PV facilities. …”
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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

“…This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. …”
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Optimal design of power system stabilizers using evolutionary programming by Abido, M.A.

“…The optimal design of power system stabilizers (PSSs) using evolutionary programming (EP) optimization technique is presented in this paper. …”
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Efficient multi-objective neural architecture search framework via policy gradient algorithm by Bo Lyu (16522643)

“…The architectures are discretely sampled by the architecture parameter α within the differentiable NAS framework, and α are directly optimised by the policy gradient algorithm. This approach eliminates the need for a sampling controller to be learned and enables the encompassment of non-differentiable metrics. …”

Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams by Eduardo Feo-Flushing (23276023)

Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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A Simulated Annealing Algorithm for System-on-Chip Test Scheduling with, Power and Precedence Constraints by Harmanani, Haidar M.

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Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

“…We present experimental results for various SOC examples that demonstrate the effectiveness of our method. The method achieved optimal test schedules in all attempted cases in a short CPU time.…”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…The support vector machine (SVM) is employed for the classification task to estimate the goodness of the selected subset of genes. The effectiveness of TRIZ optimization operators in MGWO is evaluated by investigating the convergence behavior of GWO with and without TRIZ optimization operators. …”
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Economic load dispatch multiobjective optimization procedures usinglinear programming techniques by Farag, A.

“…The validity and effectiveness of the algorithm is verified by means of two examples: a 10-bus system and the IEEE 30-Bus, six generators system…”
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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization by Alhadhrami, Esra Ebrahim

“…The Q value plays a crucial role in estimating future state values within a Kalman filter tracking system. Proximal Policy Optimization (PPO), a state-of-the-art policy optimization algorithm, was employed to determine the optimal Q value that enhances tracking performance, as measured by Root Mean Square Error (RMSE). …”
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

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A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System by Muhammad Asim (2235472)

“…Accordingly, a multi-chrome GA is adopted to find the association between UAVs and SPs, an optimal number of UAVs, and the optimal order of SPs for UAVs. …”

Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”

Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. Here, breast ultrasound (US) images are preprocessed with a sigmoid filter followed by interference-based despeckling and then by anisotropic diffusion. …”

Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective by Mir, Imran

“…This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space Exploration. …”
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A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

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Combined cycle gas turbine system optimization for extended range electric vehicles by Barakat, Aya A.

“…This study presents a methodology for the design and optimization of the most optimal combined cycle system configuration, suitable to replace the engine in a series-hybrid extended-range electric vehicle, and investigates its potential fuel savings. …”
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Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints by Bashar Hassna (19170940)

“…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …”

Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah (21399854)

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”