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241
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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242
Optimization of Battery Electric Bus Charging under Varying Operating Conditions
Published 2020“…This paper proposes an optimization algorithm based on Dynamic Programming that minimizes the total BEB energy costs and battery replacement costs by optimally controlling the BEB daily charging power throughout the year, considering the varying operating conditions. …”
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conferenceObject -
243
A new minimum curvator multi-step method for unconstrained optimization
Published 1998“…Multistep quasi-Newton methods for optimization were derived by J. A. Ford and I. A. Moghrabi [J. …”
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244
A hybrid Harris Hawks optimizer for economic load dispatch problems
Published 2022“…This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer to tackle economic load dispatch (ELD) problems. …”
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245
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246
Methods for system-on-chip test design, scheduling and optimization. (c2006)
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masterThesis -
247
A decentralized load balancing approach for parallel search-tree optimization
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conferenceObject -
248
Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization
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doctoralThesis -
249
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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250
A multi-objective planning approach for optimal DG allocation for droop based microgrids
Published 2021“…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …”
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251
Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…The Exchange Market Algorithm (EMA), initially focused on optimizing financial transactions, is considered and executed to achieve the SHM targets. …”
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252
Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System
Published 2024Subjects: -
253
Assigning proctors to exams using scatter search. (c2006)
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masterThesis -
254
Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
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doctoralThesis -
255
Exploiting Sparsity in Amplify-and-Forward Broadband Multiple Relay Selection
Published 2019Subjects: -
256
Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective
Published 2023“…This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space Exploration. …”
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257
ENUMERATIVE TECHNIQUES IN TOPOLOGICAL OPTIMIZATION OF COMPUTER NETWORKS SUBJECT TO FAULT TOLERANCE AND RELIABILITY
Published 2002“…In this paper, we propose one algorithm for optimizing the terminal reliability and another for optimizing the network reliability while improving the fault tolerance aspects of the designed networks. …”
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258
An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks
Published 2022“…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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259
A method for optimizing test bus assignment and sizing for system-on-a-chip
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conferenceObject -
260
Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization
Published 2023“…In particular, the Proximity Policy Optimization (PPO) reinforcement algorithm is used to discover a policy for sensor selection that results in optimum sensor resource allocation. …”
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