Search Results - (( processes classification using algorithm ) OR ( data classification modified algorithm ))
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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Article -
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For contextual text classification, the pre-trained LLM is further train on classificationspecific labeled data in a process called fine-tuning. …”
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Thesis -
3
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Thus, TC suggested being the main step in data pre-processing for mountainous terrain before the RBF-based SVM classification process. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Data pre-processing on the data set may improve the classification results. …”
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Final Year Project / Dissertation / Thesis -
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A hybrid spiking neural network model for multivariate data classification and visualization.
Published 2011“…This study proposes a hybrid model of Self-Organizing Map with modified adaptive coordinates (SOM-AC) and Spiking Neural Network (SNN) for multivariate spatial and temporal data visualization and classification. …”
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Proceeding -
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Modern fuzzy min max neural networks for pattern classification
Published 2019“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Thesis -
8
Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Mental Stress Classification Among Higher Education Students In Malaysia From Electroencephalogram (Eeg) Using Convolutional Neural Network With Modified Stochastic Gradient D...
Published 2024“…This study investigates the classification of mental stress among Malaysian university students using Electroencephalogram (EEG) data and a 1D-Convolutional Neural Network (1D-CNN) optimized with Modified Stochastic Gradient Descent (SGD). …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…This update process may cause the algorithm to fall to local optima especially in the cases where there are many competing local optima. …”
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Thesis -
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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15
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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