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Tool Wear Prediction Enhanced by Semantic-aware Data Compression

https://doi.org/10.2139/ssrn.6330153
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inferredcites →https://doi.org/10.1007/s00170-018-2420-0openalex-snapshot
Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process
inferredcites →https://doi.org/10.1007/s00170-023-10811-9openalex-snapshot
Tool remaining useful life prediction using bidirectional recurrent neural networks (BRNN)
inferredcites →https://doi.org/10.1007/s00170-024-14678-2openalex-snapshot
Bayesian neural networks modeling for tool wear prediction in milling Al 6061 T6 under MQL conditions
inferredcites →https://doi.org/10.1007/s10845-019-01488-7openalex-snapshot
Tool wear predicting based on multi-domain feature fusion by deep convolutional neural network in milling operations
inferredcites →https://doi.org/10.1007/s10845-019-01526-4openalex-snapshot
A hybrid information model based on long short-term memory network for tool condition monitoring
inferredcites →https://doi.org/10.1007/s12008-024-01856-5openalex-snapshot
Tribological performance in micro-milling of Ti6Al4V under nanofluid-based minimum quantity lubrication
inferredcites →https://doi.org/10.1007/s13369-023-08238-1openalex-snapshot
Performance Evaluation of TWIST Welding Using Machine Learning Assisted Evolutionary Algorithms
inferredcites →https://doi.org/10.1007/s42417-022-00776-6openalex-snapshot
Finite Element Modeling and Experimental Validation of Tool Wear in Hot-Ultrasonic-Assisted Turning of Nimonic 90
inferredcites →https://doi.org/10.1016/j.asoc.2010.10.005openalex-snapshot
Application of artificial neural network for predicting weld quality in laser transmission welding of thermoplastics
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Advanced monitoring of machining operations
inferredcites →https://doi.org/10.1016/j.cirpj.2023.11.007openalex-snapshot
Accurate prediction of five-axis machining cycle times with deep neural networks using Bi-LSTM
inferredcites →https://doi.org/10.1016/j.cirpj.2024.01.012openalex-snapshot
AI-based optimisation of total machining performance: A review
inferredcites →https://doi.org/10.1016/j.jmapro.2023.07.077openalex-snapshot
Tool wear process monitoring by damping behavior of cutting vibration for milling process
inferredcites →https://doi.org/10.1016/j.knosys.2025.112997openalex-snapshot
A Bayesian regularization neural network procedure to solve the language learning system
inferredcites →https://doi.org/10.1016/j.measurement.2024.115303openalex-snapshot
Data-driven prediction of tool wear using Bayesian regularized artificial neural networks
inferredcites →https://doi.org/10.1016/j.ymssp.2005.10.010openalex-snapshot
Estimation of tool wear during CNC milling using neural network-based sensor fusion
inferredcites →https://doi.org/10.1016/s0020-7403(01)00020-0openalex-snapshot
Modelling of cutting forces in helical end milling using a predictive machining theory
inferredcites →https://doi.org/10.1016/s0731-7085(99)00272-1openalex-snapshot
Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research
inferredcites →https://doi.org/10.1109/dcc47342.2020.00042openalex-snapshot
LFZip: Lossy Compression of Multivariate Floating-Point Time Series Data via Improved Prediction
inferredcites →https://doi.org/10.1109/ipdps.2016.11openalex-snapshot
Fast Error-Bounded Lossy HPC Data Compression with SZ
inferredcites →https://doi.org/10.1109/tbdata.2021.3066151openalex-snapshot
High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data
inferredcites →https://doi.org/10.1109/tdei.2017.006936openalex-snapshot
Bayesian regularization of neural network to predict leakage current in a salt fog environment
inferredcites →https://doi.org/10.1109/tii.2024.3353913openalex-snapshot
GreedyGD: Enhanced Generalized Deduplication for Direct Analytics in IoT
inferredcites →https://doi.org/10.1115/1.4066052openalex-snapshot
Effect of Friction on Critical Cutting Depth for Ductile–Brittle Transition in Material Removal Mechanism
inferredcites →https://doi.org/10.1145/3264903openalex-snapshot
Sprintz
inferredcites →https://doi.org/10.1145/3560814openalex-snapshot
Time Series Compression Survey
inferredcites →https://doi.org/10.1145/3626737openalex-snapshot
MOST: Model-Based Compression with Outlier Storage for Time Series Data
inferredcites →https://doi.org/10.1201/9781315373119openalex-snapshot
Metal Cutting Theory and Practice
inferredcites →https://doi.org/10.14778/3594512.3594521openalex-snapshot
Sim-Piece: Highly Accurate Piecewise Linear Approximation through Similar Segment Merging
inferredcites →https://doi.org/10.14778/3648160.3648181openalex-snapshot
PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data Compression
inferredcites →https://doi.org/10.3390/s23083833openalex-snapshot
Enhancing Tool Wear Prediction Accuracy Using Walsh–Hadamard Transform, DCGAN and Dragonfly Algorithm-Based Feature Selection
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