ICTACT Journal on Soft Computing, 2023 The present research introduces the best architectural relevance vector machine (RVM) model for predicting the compaction parameters of soil. The two types of RVM models, i.e., single kernel function-based (SRVM) and dual kernels (parallel) function-based (DRVM), have been constructed in this study. However, the RVM is a kernel function-based approach.
Jitendra Khatti, Kamaldeep Singh Grover
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Thermal Image Enhancement using Bi-dimensional Empirical Mode Decomposition in Combination with Relevance Vector Machine for Rotating Machinery Fault Diagnosis [PDF]
, 2009 In this study, a novel fault diagnosis system for rotating machinery using thermal imaging is proposed. This system consists of bi-dimensional empirical mode decomposition (BEMD) for image enhancement, a generalized discriminant analysis (GDA) for ...
Yang, Bo-Suk +7 more
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Web-Based Sustainable Detection and Treatment Recommendation System for Wheat Plant Diseases Using Convolutional Neural Networks. [PDF]
Food Sci NutrA comprehensive dataset of wheat crop images, including healthy plants and samples affected by YR and BR diseases, was developed from public sources. A Convolutional Neural Network (CNN) model was trained and optimized for accurate detection and classification of wheat diseases.
Abbasi NG +7 more
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Remaining useful life prognostics for the electro-hydraulic actuator using relevance vector machine and optimized on-line incremental learning [PDF]
MATEC Web of Conferences, 2019 The electro-hydraulic actuator plays a significant role in the automatic flight control system, so it is vital to predict the remaining useful life (RUL) for the electro-hydraulic actuators.
Dong Jiankang, Wang Jiaqi, Guo Runxia
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Sensors, 2015 Sensors play an important role in the modern manufacturing and industrial processes. Their reliability is vital to ensure reliable and accurate information for condition based maintenance.
Zhiwen Liu +3 more
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European Journal of Remote Sensing, 2021 The data classification of fully polarimetric synthetic aperture radar (PolSAR) is one of the favourite topics in the remote sensing community. To date, a wide variety of algorithms have been utilized for PolSAR data classification, and among them kernel
Iman Khosravi +3 more
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Energies, 2017 In order to improve the intelligent diagnosis level of an on-load tap-changer’s (OLTC) mechanical condition, a feature extraction method based on variational mode decomposition (VMD) and weight divergence was proposed.
Jinxin Liu +3 more
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Modeling of compressive strength of masonry structure using relevance vector machine and minimax probability machine regression [PDF]
, 2017 Compressive Strength (f) of masonry structure is a key parameter for designing masonry structure. This article employs Relevance Vector Machine (RVM) and Minimax Probability Machine Regression (MPMR) for estimation of compressive strength (f) of a ...
SAMUI PIJUSH, BOCHAROVA ANNA
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Performance Data Prognostics Based on Relevance Vector Machine and Particle Filter
Chemical Engineering Transactions, 2013 Prognostics of equipment state is one of the most important and difficult issue in Prognostics and Health Management (PHM) technology. In this paper, Relevance Vector Machine (RVM) and Particle Filter (PF) are used to analyse equipment state and predict ...
Y. Hu, P. Luo
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Fault Diagnosis of Reciprocating Compressors Using Revelance Vector Machines with A Genetic Algorithm Based on Vibration Data [PDF]
This paper focuses on the development of an advanced fault classifier for monitoring reciprocating compressors (RC) based on vibration signals. Many feature parameters can be used for fault diagnosis, here the classifier is developed based on a relevance
Gu, Fengshou +3 more
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