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A Survey of Data Clustering Techniques
Published 2023Get full text
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masterThesis -
63
Optimal design of power system stabilizers using evolutionary programming
Published 2002“…The optimal design of power system stabilizers (PSSs) using evolutionary programming (EP) optimization technique is presented in this paper. …”
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64
Optimization of PV Cleaning Practices: Comparison Between Performance-Based and Periodic-Based Approaches
Published 2020“…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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Economic load dispatch multiobjective optimization procedures usinglinear programming techniques
Published 1995“…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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Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization
Published 2023“…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...
Published 2023“…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. …”
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization
Published 2023Get full text
doctoralThesis -
71
Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks
Published 2022“…The proposed method minimizes the DR implementation cost and size, fairly incentivizes the consumers participating in the DR and priorities their consumption preferences while reduces the network power losses and DGs’ reactive power contributions to effectively manage the voltage in the MV networks. An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”
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A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017Get full text
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conferenceObject -
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Combined cycle gas turbine system optimization for extended range electric vehicles
Published 2020“…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
Published 2024“…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. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance
Published 2024“…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. …”
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Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations
Published 2021Get full text
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79
Opportunistic Throughput Optimization in Energy Harvesting Dynamic Spectrum Sharing Wireless Networks
Published 2024“…Furthermore, we propose two algorithms designed to achieve optimal throughput for each scenario. …”
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