Search Results - (( using agent based algorithm ) OR ( simulation optimization method algorithm ))
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Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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3
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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4
Finite impulse response optimizers for solving optimization problems
Published 2019“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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5
Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
Published 2024“…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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10
Modeling of static and dynamic components of bio-nanorobotic systems
Published 2012“…Moreover, agent-based behavioral models of the nanomotors are developed using state machine diagrams of UML to illustrate the internal autonomous and intelligent decision-making processes of the nanomotors. …”
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11
Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Gravitational Search Algorithm (GSA)
Published 2016“…This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…Furthermore, Optimized Parametric Topology Control Routing algorithm performs significantly better than Triangular Routing Method and Change Foreign Agent Algorithm. …”
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13
Fast PID tuning of AVR system using memory-based smoothed functional algorithm
Published 2024“…This study introduces a novel approach using a memory-based smoothed functional algorithm (MSFA) to tune the PID controller in AVR systems. …”
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Improved smoothed functional algorithmsoptimized pid controller for efficient speed regulation of wind turbines
Published 2025“…This study introduces a novel approach for PID controller tuning in wind turbine systems using single-agent optimization methods, specifically the memory smoothed functional algorithm (MSFA) and norm-limited smoothed functional algorithm (NL-SFA). …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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17
Deep Reinforcement Learning For Control
Published 2021“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation
Published 2022“…Thus, this research proposes optimization using the one of the latest nature inspired algorithm namely WOABAT-IFDO (Whale-Bat and Improved Fitness-Dependent Optimization) in the SFM interaction component. …”
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Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
Published 2016“…The performance of the hybrid SKF-PSO algorithms is compared against the original SKF using CEC2014 benchmark dataset for continuous numerical optimization problems. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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