Search Results - (( data evaluation means algorithm ) OR ( parallel optimization path algorithm ))
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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…To deal with these issues, adaptive sampling algorithm is applied to the data points to adhere to the manipulators speed constraints. …”
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors
Published 2008“…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…The algorithms applied separately with (1) Mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean. …”
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…Our methodology incorporated ontology to filter the datasets and exploited Rapidminer environment to evaluate the performance of clustering algorithms. …”
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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The performances ofthese aggregation algorithms ofNNs ensemble were evaluated with the mean absolutepercentage error and symmetric mean absolute percentage error. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques
Published 2017“…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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Centre-based hard clustering algorithms for Y-STR data / Ali Seman, Zainab Abu Bakar and Azizian Mohd. Sapawi
Published 2010“…The three algorithms above are experimented and evaluated in partitioning Y-STR haplogroups and Y-STR Surname data. …”
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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Noise is one of the obstacles for brain MRI segmentation. The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Hybridizing the Deep Neural Network (DNN) with the K-Means Clustering algorithm will increase the accuracy and reduce the data complexity of the Lorenz dataset. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting
Published 2013“…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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