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Evolutionary Game-Based Battery Scheduling: A Comparative Study for Prosumers in Smart Grids
Published 2025“…A comprehensive comparative analysis is conducted between the proposed EGT algorithm and established methods such as centralized optimization (CO), game theory (GT), and auction-based approaches. …”
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Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
Published 2024“…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”
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Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors
Published 2016“…Finally, using the developed design models and simulation algorithms, constrained non-linear multi-variable geometric optimization of the assembly components has been carried out to obtain minimum pumping power, maximum extractor heat transfer coefficient, and maximum thermoelectric power output. …”
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A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System
Published 2023“…In this regard, this paper is the first report in the literature demonstrating the implementation of a real PIDD2 controller for controlling the respective system. We construct a novel and efficient metaheuristic algorithm by improving the performance of the Aquila Optimizer via chaotic local search and modified opposition-based learning strategies and use it as an excellently performing tuning mechanism. …”
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An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
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Fuzzy simulated evolution algorithm for VLSI cell placement
Published 2003“…There has not been a consensus on how to accommodate all these (conflicting) requirements in the search for near optimal feasible solutions. In this paper, we present a fuzzy simulated evolution (FSE) algorithm to tackle this problem. …”
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Mobile Robot Navigation in Dynamic Environments Using an Improved RRT* Approach
Published 2018Get full text
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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems
Published 2024“…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability
Published 2025“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”
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Detecting sleep outside the clinic using wearable heart rate devices
Published 2022“…Against sleep diaries, the algorithm yielded a mean squared error of 0.04–0.06 and a total sleep time (TST) deviation of - 2.70 (± 5.74) and 12.80 (± 3.89) minutes, respectively. …”
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An Adaptive Sliding Mode Control for a Dual Active Bridge Converter With Extended Phase Shift Modulation
Published 2023“…The conventional single-phase shift (SPS) modulation-based DAB converter is known to be inefficient. Hence, an optimization algorithm based on the Lagrange multiplier method (LMM) is proposed to minimize both backflow power and inductor current stress simultaneously. …”
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Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas
Published 2024“…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …”
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Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation
Published 2024“…From this perspective, this paper proposes an efficient framework for fast and optimal PGP, based on singular value decomposition analysis of the graph's Laplacian. …”
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”