Search Results - (( variable information using algorithm ) OR ( java application reoptimize algorithm ))
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EMS decoding algorithm that introduced shuffled strategy and improved variable node update
Published 2022“…This algorithm updates by column, so that the latest variable node information of the last column can be used. …”
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An algorithm for pulsed activation of solenoid valves for variable rate application of agricultural chemicals
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…The fixed block matching uses the same block size throughout the motion estimation process while the variable block matching uses different block size. …”
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5
Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…The Bayesian logistic regression methods made use of the metropolis hasting (Random walk algorithm) and the Gibbs sampler with the incorporation of non-informative flat prior and non-informative non-flat prior distributions to obtain the posterior distribution for each coefficient of the variables. …”
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9
Optimized clustering with modified K-means algorithm
Published 2021“…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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10
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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11
Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…First, the flower pollination algorithm is applied to search for informative spectral variables, followed by variable elimination. …”
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What drives Chinese youth to use fitness-related health information on social media? an analysis of intrinsic needs, social media algorithms, and source credibility
Published 2024“…Results: The analysis revealed that all three intrinsic needs—competence, autonomy, and relatedness—along with social media algorithms and source credibility, positively correlated with fitness-related health information use behaviors among youth. …”
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Integrated ACOR/IACOMV-R-SVM Algorithm
Published 2017“…Three benchmark UCI datasets were used in the experiments to validate the performance of the proposed algorithms. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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Road Sign Detection and Recognition System for Real-Time Embedded Applications
Published 2011“…The characteristics of the shapes such as area and perimeter variables are used to identify the symbols in the road signs. …”
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Improved Variable Neighbourhood Descent (VND) to Solve Universiti Malaysia Sarawak (UNIMAS) Course Timetabling Problem
Published 2023“…A two-stage heuristic algorithm is proposed. In stage 1, heuristic orderings were utilised to find a feasible solution using 31 timeslots instead of the 48 timeslots in the existing timetabling software. …”
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Path optimization using genetic algorithm in laser scanning system
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Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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