Search Results - (( parameter estimation model algorithm ) OR ( sequence optimization based algorithm ))
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Book Chapter -
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
Conference Paper -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…The adaptive control structure is based on the linear model of the process and combined with numerical algorithm for subspace state space system identification (N4SID). …”
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Conference or Workshop Item -
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Conceptual Design And Dynamical Analysis Of Aerostat System
Published 2020“…The aerostat is modeled as a single rigid body while the tether has been modeled as a sequence of elements connected at nodes through a revolute degree of freedom. …”
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Thesis -
7
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
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Article -
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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Thesis -
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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A new metaphor-less algorithms for the photovoltaic cell parameter estimation
Published 2023Article -
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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UMK Etheses -
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Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway
Published 2023“…Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. …”
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Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies
Published 2009“…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…The estimated parameters from the experiment produce a better model by means of obtaining a reasonable good fit of model prediction to the experimental data. …”
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Article -
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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Product assembly sequence optimization based on genetic algorithm
Published 2010“…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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Article -
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In addition, building a kinetic model requires the estimation of the kinetic parameters, but kinetic parameters estimation in kinetic modeling is a difficult task due to the nonlinearity of the model. …”
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Article -
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Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…The required memory of this algorithm is also time independent. In addition, the optimal state sequence obtained by the EVRA algorithm is the same as that obtained by the classical Viterbi algorithm for HHMM.…”
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