Robust neural networks with random weights based on generalized M-estimation and PLS for imperfect industrial data modeling
Sign Up to like & getrecommendations! Published in 2020 at "Control Engineering Practice"
DOI: 10.1016/j.conengprac.2020.104633
Abstract: Abstract Actual industrial data inevitably contain a variety of outliers for various reasons. Even a single outlier may have a large distortion effect on modeling performance with conventional algorithms, not to mention the complicated process… read more here.
Keywords: generalized estimation; industrial data; robust neural; imperfect industrial ... See more keywords
What Works, What Doesn't, and Why? An Industrial Perspective on Absorption Modeling.
Sign Up to like & getrecommendations! Published in 2025 at "Journal of medicinal chemistry"
DOI: 10.1021/acs.jmedchem.5c00744
Abstract: Lead optimization failures are often linked to poor absorption, compounded by efflux transport and low recovery. We report a comprehensive modeling of public and industrial data on organic molecules' absorption. Comparative analysis of an industrial… read more here.
Keywords: absorption modeling; industrial perspective; works industrial; perspective absorption ... See more keywords
WrapperRL: Reinforcement Learning Agent for Feature Selection in High-Dimensional Industrial Data
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3456688
Abstract: Finding the set of discriminatory features in a classification task is imperative for the interpretability of the “black box” deep learning (DL) models, especially in high-stakes industrial applications such as predictive maintenance and industrial noise… read more here.
Keywords: learning agent; interpretability; reinforcement learning; industrial data ... See more keywords
Joint Scheduling of IEEE 802.1AS gPTP and Industrial Data Traffic in TSN-6G Networks
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3577021
Abstract: The 6th Generation (6G) mobile network is envisaged to play a significant role for supporting time-sensitive applications in industrial scenarios. The integration between 6G and (wired) Ethernet Time-Sensitive Networking (TSN) is a natural step to… read more here.
Keywords: data traffic; time; tsn; ieee 802 ... See more keywords
Augmented Industrial Data-Driven Modeling Under the Curse of Dimensionality
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2023.123396
Abstract: The curse of dimensionality refers to the problem of increased sparsity and computational complexity when dealing with high-dimensional data. In recent years, the types and variables of industrial data have increased significantly, making data-driven models… read more here.
Keywords: augmented industrial; industrial data; curse dimensionality; data driven ... See more keywords
Mixed-criticality Industrial Data Scheduling on 5G NR
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3121251
Abstract: Compared to industrial wired networks, 5G can improve device mobility and reduce the cost of networking. However, the real-time performance and reliability of 5G NR (new radio) still need to be improved to satisfy industrial… read more here.
Keywords: criticality; performance; mixed criticality; industrial data ... See more keywords
A New Particle Swarm Optimization Algorithm for Outlier Detection: Industrial Data Clustering in Wire Arc Additive Manufacturing
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Automation Science and Engineering"
DOI: 10.1109/tase.2022.3230080
Abstract: In this paper, a novel outlier detection method is proposed for industrial data analysis based on the fuzzy C-means (FCM) algorithm. An adaptive switching randomly perturbed particle swarm optimization algorithm (ASRPPSO) is put forward to… read more here.
Keywords: detection; outlier detection; particle swarm; industrial data ... See more keywords
A Robust Fault Classification Method for Streaming Industrial Data Based on Wasserstein Generative Adversarial Network and Semi-Supervised Ladder Network
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3262249
Abstract: With the development of modern information technology, the collection, storage, and transmission of information in the process industry have been gaining popularity. However, the massive streaming industrial data obtained in real time have some nonideal… read more here.
Keywords: network; streaming industrial; classification; industrial data ... See more keywords
InterGCNet: An Interpolation Geometric Constructive Neural Network for Industrial Data Modeling
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2024.3470037
Abstract: For industrial data modeling, how to build data-driven models on resource-constrained industrial devices is a research hotspot. However, existing literature is either high resource consumption or poor prediction performance. To bridge this gap, we propose… read more here.
Keywords: geometric constructive; interpolation geometric; data modeling; industrial data ... See more keywords
Blockchain Assisted Industrial Data Registration and Reconstruction Management Scheme
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2025.3547409
Abstract: As a typical Industrial Internet of Things (IIOT) application, three-dimensional point cloud reconstruction brings us benefits and convenience. The reconstructed mathematical models can be employed to facilitate precise quality control, which is important for the… read more here.
Keywords: registration; reconstruction; blockchain assisted; industrial data ... See more keywords
Composition-Processing-Property Correlation Mining of Nb–Ti Microalloyed Steel Based on Industrial Data
Sign Up to like & getrecommendations! Published in 2020 at "Materials Transactions"
DOI: 10.2320/matertrans.mt-m2019172
Abstract: Modeling strength of hot rolled strip based on industrial data may cause misleading predictions because of the high dimension, low quality and unbalanced original data. Industrial data processing is essential to building a successful composition-process-property… read more here.
Keywords: based industrial; correlation; microalloyed steel; property ... See more keywords