Search Results - (( parallel estimation method algorithm ) OR ( variable generation learning algorithm ))
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Parallel visualization approach of a 3D heart model
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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems
Published 2016“…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China
Published 2024“…Machine learning models have been effectively applied to predict certain variable in several engineering applications where the variable is highly stochastic in nature and complex to identify utilizing the classical mathematical models. …”
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition
Published 2007“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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Early detection of breast cancer using wave elliptic equation with high performance computing
Published 2008“…This paper focuses on the implementation of parallel algorithm for the simulation of breast cancer tumor using two dimensional Helmholtz’s wave equation on a distributed parallel computer system (DPCS). …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…The model is, essentially, a dynamic Bayesian network induced from manually annotated dialogue corpus via dynamic Bayesian machine learning algorithms. Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia
Published 2025“…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. The machine learning algorithms investigated are specifically Gaussian process regression (GPR), ensemble of trees and neural networks. …”
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Image reconstruction using iterative transpose algorithm for optical tomography
Published 2007“…This paper describes a transpose algorithm for use with an optical tomography system. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Iterative methods for solving split common fixed point problems in Hilbert spaces
Published 2016“…In other words, we construct parallel and cyclic algorithms for solving the split common fixed point problems for strictly pseudocontractive mappings and prove the convergence results of these algorithms. …”
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Enhancing wind power forecasting accuracy with hybrid deep learning and teaching-learning-based optimization
Published 2024“…This paper presents an innovative approach that combines deep learning (DL) with Teaching-Learning-Based Optimization (TLBO) to predict wind power output accurately. …”
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A bayesian network approach to identify factors affecting learning of Additional Mathematics
Published 2015“…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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