Search Results - (( variables classification using algorithm ) OR ( variable generation using algorithm ))
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1
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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2
Using fuzzy association rule mining in cancer classification
Published 2011“…At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. …”
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3
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…The proposed hybrid MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher's Iris data set and shown to be very competitive.…”
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4
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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5
Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. The Simplex algorithm has three stages of computation namely initialization, iterative calculation and termination. …”
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6
Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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7
Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis
Published 2017“…Results: By using the ID3 algorithm, it is possible to consider the relationship among variables and to identify the most informative variables for predicting the classification of the instance. …”
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8
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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9
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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10
Comparison of meta-heuristic algorithms for fuzzy modelling of covid-19 illness’ severity classification
Published 2022“…The performance of the five meta-heuristic algorithms was evaluated using the COVID-19 symptoms dataset. …”
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11
Ensemble learning for multidimensional poverty classification
Published 2020“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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12
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…Classifier algorithms, namely the Support Vector Machine and K-Nearest Neighbours were used for benchmarking the performance of the Real-Valued Negative Selection Algorithms. …”
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13
Novel techniques for enhancement and segmentation of acne vulgaris lesions
Published 2013“…The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. …”
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14
A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…This paper proposed to generate solution for Particle Swarm Optimization (PSO) algorithms using Ant Colony Optimization approach, which will satisfy the Gaussian distributions to enhance PSO performance. …”
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15
An evolutionary based features construction methods for data summarization approach
Published 2015“…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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16
Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…Fifteen test functions with different initial points and variables ranged from 2 to 10,000 variables are chosen. …”
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17
Detection of Denial of Service Attacks against Domain Name System Using Neural Networks
Published 2009“…With the prior knowledge of DoS attacks against DNS, we used a network simulator to model DNS traffic with high variability. …”
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18
Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)
Published 2023“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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19
Advanced neural networking and classification techniques for human brain tissues diagnoses: segmenting healthy, cancer affected and edema brain tissues
Published 2019“…Especially, in this work MRI images are used to diagnose tumor in the brain. However, the huge amount of data generated by MRI scan thwarts manual classification of tumor vs non-tumor in a particular time. …”
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20
Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)
Published 2023“…Next, the grades of concrete were classified using a machine learning algorithm named k-Nearest Neighbour (k-NN). …”
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