Zhang et al., 2024 - Google Patents
A hybrid artificial intelligence algorithm for fault diagnosis of hot rolled strip crown imbalanceZhang et al., 2024
- Document ID
- 12788591435812015814
- Author
- Zhang R
- Qi Y
- Kong S
- Wang X
- Li M
- Publication year
- Publication venue
- Engineering Applications of Artificial Intelligence
External Links
Snippet
In the production process of hot continuous rolling, due to the imbalance between the number of normal cases and fault cases, the traditional supervised learning methods are often unable to deal with them efficiently. In order to address this problem, a new Hybrid …
- 238000003745 diagnosis 0 title abstract description 64
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/01—Social networking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F7/00—Methods or arrangements for processing data by operating upon the order or content of the data handled
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F15/00—Digital computers in general; Data processing equipment in general
- G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Li et al. | A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction | |
Bai et al. | A manufacturing quality prediction model based on AdaBoost-LSTM with rough knowledge | |
Li et al. | A review on physics-informed data-driven remaining useful life prediction: Challenges and opportunities | |
Moya et al. | Deeponet-grid-uq: A trustworthy deep operator framework for predicting the power grid’s post-fault trajectories | |
Du et al. | Exploration of financial market credit scoring and risk management and prediction using deep learning and bionic algorithm | |
Al-Dulaimi et al. | NBLSTM: Noisy and hybrid convolutional neural network and BLSTM-Based deep architecture for remaining useful life estimation | |
Zanjirchi et al. | Four decades of fuzzy sets theory in operations management: application of life-cycle, bibliometrics and content analysis | |
Zhang et al. | A hybrid artificial intelligence algorithm for fault diagnosis of hot rolled strip crown imbalance | |
Li et al. | A Gaussian mixture model based virtual sample generation approach for small datasets in industrial processes | |
Yin et al. | An integrated computational intelligence technique based operating parameters optimization scheme for quality improvement oriented process-manufacturing system | |
Sun et al. | A causal model-inspired automatic feature-selection method for developing data-driven soft sensors in complex industrial processes | |
Jia et al. | Transfer learning for end-product quality prediction of batch processes using domain-adaption joint-Y PLS | |
Zhang et al. | An attention-based temporal convolutional network method for predicting remaining useful life of aero-engine | |
Luo et al. | A weighted SVM ensemble predictor based on AdaBoost for blast furnace ironmaking process | |
Liu et al. | Product quality prediction method in small sample data environment | |
Yang et al. | A bidirectional recursive gated dual attention unit based RUL prediction approach | |
Hao et al. | Prediction of electricity consumption in cement production: a time-varying delay deep belief network prediction method | |
Cheng et al. | A health state-related ensemble deep learning method for aircraft engine remaining useful life prediction | |
Zhang et al. | A framework for predicting the remaining useful life of machinery working under time-varying operational conditions | |
Song et al. | Three-reference-point decision-making method with incomplete weight information considering independent and interactive characteristics | |
He et al. | A decomposition-based multi-objective particle swarm optimization algorithm with a local search strategy for key quality characteristic identification in production processes | |
Danti et al. | A methodology to determine the optimal train-set size for autoencoders applied to energy systems | |
Wang et al. | Hierarchical graph neural network with adaptive cross-graph fusion for remaining useful life prediction | |
Ren et al. | Time-varying Gaussian Encoder based Adaptive Sensor-Weighted Method for Turbofan Engine Remaining Useful Life Prediction | |
Ma et al. | Transformer based Kalman Filter with EM algorithm for time series prediction and anomaly detection of complex systems |