Search Results - (( data classification modified algorithm ) OR ( data application using algorithm ))
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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Thesis -
4
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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5
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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Logistic regression methods for classification of imbalanced data sets
Published 2012“…The imbalanced problem of both proposed general classification algorithms which is the limitation of accuracy performance specifically in classifying on the minority class has motivated this research to improve their classification performance on imbalanced data sets. …”
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7
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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Automated classification of blasts in acute leukemia blood samples using HMLP network
Published 2011“…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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Conference or Workshop Item -
9
A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping
Published 2016“…The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. …”
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Analysis of multicomponent transient signals using music superresolution technique
Published 2008“…A new method of analysis using modified MUSIC (multiple signal classification) subspace algorithm is successfully applied to the analysis of this signal. …”
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Proceeding Paper -
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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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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan
Published 2023“…The project follows a modified waterfall approach, focusing on creating a user-friendly interface and integrating the Random Forest Classification Algorithm for accurate detection. …”
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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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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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16
Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion
Published 2017“…The proposed algorithm takes input data from multichannel EEG timeseries, which is also known as multivariate pattern analysis. …”
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Article -
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Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…Unlike the commercial ECG simulators, to the best of our knowledge, there is no such commercially available system that can be used for such research tasks. With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…However, numerous data mining techniques have been successfully applied in this area to find intrusions hidden in large amounts of audit data through classification, clustering or association rule. …”
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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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