Search Results - (( estimation using grey algorithm ) OR ( java implication based algorithm ))
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica...
Published 2021“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. …”
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Single-agent finite impulse response optimizer for numerical optimization problems
Published 2018“…The performance of the SAFIRO algorithm is evaluated using the CEC 2014 Benchmark Test Suite for single-objective optimization and statistically compared with the several well-known metaheuristic optimization algorithms, such as Particle Swarm Optimization algorithm, Genetic Algorithm, and Grey Wolf Optimization algorithm. …”
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Cubature kalman optimizer : A novel metaheuristic algorithm for solving numerical optimization problems
Published 2023“…In control system, the CKF algorithm is used to estimate the true value of a hidden quantity from an observation signal that contain an uncertainty. …”
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INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
Published 2023“…First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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Thesis -
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Also, a filter-based image inhomogeneity-correction algorithm is proposed which uses the maximum filter for inhomogeneity field estimation. …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators
Published 2025“…These algorithms play a crucial role in estimating the optimal values of Kp, Ki, and Kd for the PID speed controller, as well as Kp and Ki for the PI controller used in the flux, DC-link voltage, and grid connection for wind energy conversion system based dual-star induction generator. …”
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System identification of parameterized state-space model of a small scale UAV helicopter
Published 2012“…Considering the complexity of the helicopter dynamics, and inherent di�culty involves with physical measurement of the system parameters, the grey modeling approach which involves the development of parameterized model from �rst principles and estimation of these parameters using system identi�cation (sysID) technique has been proposed in the literatures. …”
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Proceeding Paper -
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Automated Model Generation Approach Using MATLAB
Published 2011“…The aim of the chapter is to introduce a self-tuning algorithm (i.e., AMG) using MATLAB for automated analogue circuit modelling suitable for HLM and HLFM applications. …”
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Book Section -
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A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis
