Search Results - optimal ((((step algorithm) OR (based algorithm))) OR (((system algorithm) OR (search algorithm))))
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1
Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system
Published 2022“…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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2
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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3
Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS
Published 2015“…The constant step size in the original bacterial foraging algorithm causes oscillation in the convergence graph where bacteria are not able to reach the optimum location with large step size, hence reducing the accuracy of the final solution. …”
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4
A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…SKF is a random based optimization algorithm inspired from Kalman Filter theory. …”
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5
An Efficient Control Implementation for Inverter Based Harmony Search Algorithm
Published 2017“…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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6
A Kalman-Filter-Based Sine-Cosine Algorithm
Published 2019“…SKF is a random based optimization algorithm inspired from the Kalman Filter theory. …”
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7
Novel Hybrid Bacterial Foraging and Spiral Dynamics Algorithms
Published 2013“…This paper presents three novel hybrid optimization algorithms based on bacterial foraging and spiral dynamics algorithms and their application to modelling of flexible maneuvering systems. …”
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8
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Model structure selection is one of the important steps in a system identification process. Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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9
An exponential based simulated kalman filter algorithm for data-driven PID tuning in liquid slosh controller
Published 2018“…SKF is a random based optimization algorithm inspired from a Kalman Filter theory. …”
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10
Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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12
Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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13
Iteration strategy and ts effect towards the performance of population based metaheuristics
Published 2020“…In single solution based algorithms, the steps are executed one by one by the single search agent. …”
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14
Adaptive sine-cosine algorithms for global optimization
Published 2018“…The algorithms performance in terms of their achievement of finding a near optimal solution is analyzed and discussed. …”
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15
Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
Published 2014“…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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16
An efficient control implementation for inverter based harmony serach algorithm
Published 2017“…This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. …”
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17
Using artificial intelligence search in solving the camera placement problem
Published 2022“…The chapter also carries out an analytical review of three main searching algorithms namely, generate and test, uninformed search, and hill climbing search algorithms. …”
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18
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…However, conventional PSO is prone to lack of convergence and even stagnation in complex high dimensional-search problems with multiple local optima. Therefore, this research proposed an improved Mutually-Optimized Fractional PSO (MOFPSO) algorithm based on fractional derivatives and small step lengths to ensure convergence to global optima by supplying a fine balance between exploration and exploitation. …”
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19
Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Published 2023“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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