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A semi-supervised method for digital twin-enabled predictive maintenance in the building industry
The rapid booming of information and communication technologies (ICT) and artificial intelligence has promoted the development of maintenance...
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Chronologically Guided Deep Network for Remaining Useful Life Estimation
In this paper, we introduce a new chronological loss function for training models to predict remaining useful life (RUL) of industrial assets based...
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Theoretical Foundations, Methods, and Algorithms for Lossless-in-Sense Text Compression
AbstractThe article is devoted to the scientific school developed by the first author in 1995–2012 in Yaroslav-the-Wise Novgorod State University...
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Reinforcement learning for predictive maintenance: a systematic technical review
The manufacturing world is subject to ever-increasing cost optimization pressures. Maintenance adds to cost and disrupts production; optimized...
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Novel direct remaining useful life estimation of aero-engines with randomly assigned hidden nodes
This paper aims to improve data-driven prognostics by presenting a novel approach of directly estimating the remaining useful life (RUL) of...
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Modeling Distributed and Flexible PHM Framework Based on the Belief Function Theory
This paper explores the integration of the belief function theory within the domain of Prognostics and Health Management (PHM), offering a novel...
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Attention and Relative Distance Alignment for Low-Resolution Facial Expression Recognition
In real-world scenarios, facial images obtained by many devices often exhibit low resolution. However, the performance significantly degrades when we...
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An Online Data-Driven Predictive Maintenance Approach for Railway Switches
An online data-driven predictive maintenance approach for railway switches using data logs obtained from the interlocking system of the railway...
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A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines
The past decade has witnessed the adoption of artificial intelligence (AI) in various applications. It is of no exception in the area of prognostics...
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Moth flame algorithm-based optimization of a reduced switch multilevel inverter topology suitable for standalone application
The escalating demand for sustainable and environmentally friendly energy sources has driven substantial growth in renewable energy adoption across...
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ASM: Adaptive Sample Mining for In-The-Wild Facial Expression Recognition
Given the similarity between facial expression categories, the presence of compound facial expressions, and the subjectivity of annotators, facial...
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A Hybrid Data-Driven Approach for Predicting Remaining Useful Life of Industrial Equipment
Guaranteeing the safety of equipment is extremely important in industry. To improve reliability and availability of equipment, various methods for...
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Empirical Mode Decomposition and Temporal Convolutional Networks for Remaining Useful Life Estimation
Remaining useful life (RUL) prediction plays an important role in guaranteeing safe operation and reducing maintenance cost in modern industry. In...
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Research on Long Life Product Prognostics Technology Based on Deep Learning and Statistical Information Fusion
The simple use of reliability statistical models to predict the remaining life of products lacks specific information about equipment performance...
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A Study on Predictive Maintenance System for Industrial Robot RV Reducers Based on AI and ROM
Industrial robots are the core equipment of process automation and are becoming increasingly important in smart factories triggered by the Fourth...
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Local Search for Integrated Predictive Maintenance and Scheduling in Flow-Shop
We address the Permutation Flow-Shop Scheduling Problem with Predictive Maintenance presented by Varnier and Zerhouni (2012), that consists in...
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Co** with Increased Levels of Label Noise in Facial Expression Recognition
An important problem in facial expression recognition (FER) is the presence of inaccurate annotations referred to as noisy annotations in the...
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XGBoost based residual life prediction in the presence of human error in maintenance
Accurate maintenance decision making is essential for organizations like military and aviation. Immensely demanding situations like limited time...
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Exploiting Context and Attention Using Recurrent Neural Network for Sensor Time Series Prediction
In the current era of Internet of Things, typically data from multiple sources are captured through various sensors yielding Multivariate Time Series...
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A survey of transfer learning for machinery diagnostics and prognostics
In industrial manufacturing systems, failures of machines caused by faults in their key components greatly influence operational safety and system...
