Search Results - (( using classification clustering algorithm ) OR ( using function method algorithm ))
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1
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…Clustering is an unsupervised classification method with major aim of partitioning, where objects in the same cluster are similar, and objects belong to different clusters vary significantly, with respect to their attributes. …”
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3
A review: accuracy optimization in clustering ensembles using genetic algorithms
Published 2011“…This paper concludes that using genetic algorithms in clustering ensemble improves the clustering accuracy and addresses open questions subject to future research.…”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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7
Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…Although the neural network methods are not very effective in clustering biologically active structures, their performance is remarkable when used as classifiers. …”
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…Hence, MKS-SSVM is extended for multiclass classification. Two popular multiclass classification methods One against All (OAA) and One against One (OAO)) were used to extend MKS-SSVM. …”
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9
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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10
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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11
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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12
A study on component-based technology for development of complex bioinformatics software
Published 2004“…SOM and K-Means are integrated as a clustering algorithm to produce a granular input, while SVM is then used as a classifier. …”
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13
Implementation of vision-assisted path planning system for bulk die sorting in semiconductor industry
Published 2018“…Firstly, the wafer image is acquired using the image mosaicing method. Then, die classification is performed to obtain the positions of functional and non-functional dies. …”
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Implementation of vision-assisted path planning system for bulk die sorting in semiconductor industry
Published 2018“…Firstly, the wafer image is acquired using the image mosaicing method. Then, die classification is performed to obtain the positions of functional and non-functional dies. …”
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15
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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17
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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18
A framework for predicting oil-palm yield from climate data
Published 2006“…At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration
Published 2014“…A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. …”
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20
Face emotion recognition using artificial intelligence techniques
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