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A novel hybrid methodology for fault diagnosis of wind energy conversion systems
Published 2023“…The proposed technique involved two major steps: feature selection and fault classification. …”
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Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…The performance of our approach is gauged against the traditional multi-label Naïve Bayes (MLNB) algorithm and is quantified through a suite of evaluation metrics. …”
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A machine learning model for early detection of diabetic foot using thermogram images
Published 2021“…A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting.…”
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The failures encompassed in this study are the open-circuit/short-circuit, islanding, output current sensor, and partial shading faults. In the proposed FDD approach, named interval reduced kernel PCA (IRKPCA)-based Random Forest (IRKPCA-RF), the feature extraction and selection phase is performed using the IRKPCA models while the fault classification is ensured using the RF algorithm. …”
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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization
Published 2022“…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …”
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67
A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…For this purpose, a combination of Decisive Red Fox (DRF) Optimization and Descriptive Back Propagated Radial Basis Function (DBRF) classification are developed in the proposed work. The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”
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68
Fast fractal stack: fractal analysis of computed tomography scans of the lung
Published 2011“…The proposed approach performs well, improving the classification accuracy when compared to other feature extraction algorithms. …”
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69
Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. …”
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A Multistage Passive Islanding Detection Method for Synchronous-Based Distributed Generation
Published 2021“…A multistage approach to passive islanding detection is proposed that utilizes a decision tree (DT) like classification algorithm. …”
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Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…In this paper, deepConvolutionalNeuralNetwork(CNN)withDwarfMongooseoptimizedResidualNetwork(DM ResNet) is proposed for the classification of autism disorder from Magnetic Resonance Imaging (MRI) brain images. …”
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Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…High resolution signal processing techniques involving higher-order statistics (HOS) and artificial neural networks (ANN) which re useful in ultrasonic nondestructive evaluation (NDE) of materials systems subject to additive white Gaussian noise (AWGN) and masking effects of measurement systems used and propagation paths, are investigated in this Thesis. The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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Adaptive false discovery rate for wavelet denoising of pavement continuous deflection measurements
Published 2016“…When tested in a simulation study, the results of the proposed algorithm compared favorably with other state-of-the-art methods. …”
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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems
Published 2020“…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…The primary goals of feature selection are to decrease the number of dimensions and enhance classification accuracy in many domains, such as text classification, large-scale data analysis, and pattern recognition. …”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. …”
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Impact Of Inspection Errors On The Performance Measures Of A General: Repeat Inspection Plan
Published 2020“…An inspection plan for such components has been proposed in quality control tat deals with several types of classification errors made by the inspector. …”
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