A comparison of optimization heuristics for the data mapping problem by Mansour, Nashat

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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

“…In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …”

A Survey of Data Clustering Techniques by Sobeh, Salma

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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques by Arifa Zahir (20748764)

“…LeNet demonstrates optimized accuracy in classifying the records, outperforming CNN by 52% and Inception-V3 by 70%. …”

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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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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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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Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks by Islambouli, Rania

“…We formulate the problem as a mixed integer program, and propose an efficient meta-heuristic solution based on the ions motion optimization algorithm. The performance of the meta-heuristic solution is evaluated and compared to the optimal solution as a function of various system parameters and for different application use cases. …”
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Economic load dispatch multiobjective optimization procedures usinglinear programming techniques by Farag, A.

“…This paper outlines the optimization problem of real and reactive power, and presents the new algorithm for studying the load shedding and generation reallocation problem in emergencies where a portion of the transmission system is disabled and an AC power solution cannot be found for the overloaded system. …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

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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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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg... by Ali S. Alghamdi (12722891)

“…The performance of the IFLA when applied to EH coordinated scheduling and management problems with the aim of profit maximization is compared with the conventional FLA, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. …”

Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization by Hafez, Ishaq

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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. …”

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

“…The station is modelled using building-information modelling (BIM) software, wherein all of the station’s models are gathered and linked using BIM software to illustrate the BIPV and indicate the solar insolation distribution on the rooftop by simulating the station’s rooftop. The system is optimised for maximum yield to determine the optimal configuration and number of modules for each string using a genetic algorithm. …”

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. …”

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. …”