Search Results - (( data classification modeling algorithm ) OR ( data normalization based algorithm ))
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1
Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
Published 2021“…In this article, the classification of cardiac abnormalities from electrocardio�gram medical data has been carried out using the Fuzzy Cognitive Map (FCM) approach. …”
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2
Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
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Student Project -
3
Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Thesis -
4
SVM for network anomaly detection using ACO feature subset
Published 2016“…Classification approach has been widely adopted for the development of the anomaly detection model to classify the data into normal class and attack class. …”
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5
Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm
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6
Risk management credit scoring prediction using sentiment analysis
Published 2024“…The project adopts a development-based approach with field of data science, leveraging NLP techniques and classification algorithms to seamlessly integrate sentiment-derived features with conventional credit scoring attributes. …”
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Final Year Project / Dissertation / Thesis -
7
Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data
Published 2011“…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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Article -
8
Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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9
An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…On the contrary, CF+N technique requires some enhancements as the results were below expectations because of the tendency of CF to produce big differences in the prediction of raw data. It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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Thesis -
10
A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
11
EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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Citation Index Journal -
12
Effective gene selection techniques for classification of gene expression data
Published 2005“…The selected subset of genes is then be used to train the classifiers for constructing rules for future tissue classification problem. Various k-means clustering algorithms and model-based clustering algorithms are proposed to group the genes. …”
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Thesis -
13
Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…Preprocessing ML steps including converting class numbers to strings, identifying and removing missing values, partitioning and normalizing data were implemented prior to the development of the model. …”
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14
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…DWT was used to analyze EEG signals at different frequency bands and statistics over the set of the wavelet coefficients were calculated to introduce the feature vector for SNS classifier. The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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15
VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams
Published 2023“…In this study, we conducted a comparison of two versions of the VGG16-based deep learning model for breathing sound classification using Gammatonegrams as input. …”
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Conference or Workshop Item -
16
Anomaly behavior detection using flexible packet filtering and support vector machine algorithms
Published 2016“…The Entropy and SVM (EaSVM) is relying on DARPA 99 dataset for analyzing the captured traffics based on anomalies and the use of SVM is to classify the entropy values of the data traffic into normal and abnormal behavior for more accurate results. …”
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17
Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. …”
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Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine
Published 2022“…Classification is an essential task for many applications, including text classification, image classification, data classification, and so on. …”
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19
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
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Thesis -
20
Converged Classification Network For Matching Cost Computation
Published 2020“…Stereoscopic vision lets us identify the world around us in 3D by incorporating data from depth signals into a clear visual model of the world. …”
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