117 results on '"Kulahci, Murat"'
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2. Real-Time Sampling Strategies for Regression with Irrelevant Features
3. Autonomous Anomaly Detection and Handling of Spatiotemporal Railway Data
4. Forecasting Operational Conditions: A case-study from dewatering of biomass at an industrial wastewater treatment plant
5. Statistical process control versus deep learning for power plant condition monitoring
6. Big Data Generation for Time Dependent Processes: The Tennessee Eastman Process for Generating Large Quantities of Process Data
7. Hidden dimensions of the data: PCA vs autoencoders
8. Variable selection wrapper in presence of correlated input variables for random forest models
9. Robust online active learning
10. Application of Machine Learning for Prediction and Process Optimization—Case Study of Blush Defect in Plastic Injection Molding
11. Online monitoring for error detection in vat photopolymerization
12. Rare-Events Classification: An Approach Based on Genetic Algorithm and Voronoi Tessellation
13. Stream-based active learning with linear models
14. Transient risk of water layer formation on PCBAs in different climates: Climate data analysis and experimental study
15. A climate classification for corrosion control in electronic system design
16. A novel fault detection and diagnosis approach based on orthogonal autoencoders
17. A numerical study of Markov decision process algorithms for multi-component replacement problems
18. A taxonomy of railway track maintenance planning and scheduling: A review and research trends
19. Classification Methods for Market Making in Auction Markets
20. Surveillance of Antidepressant Safety (SADS): Active Signal Detection of Serious Medical Events Following SSRI and SNRI Initiation Using Big Healthcare Data
21. An easy to use GUI for simulating big data using Tennessee Eastman process
22. An extended Tennessee Eastman simulation dataset for fault-detection and decision support systems
23. Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 2–Comparison of the Performance of Artificial Intelligence and Traditional Pharmacoepidemiological Techniques
24. Cost-sensitive learning classification strategy for predicting product failures
25. Mould wear-out prediction in the plastic injection moulding industry: a case study
26. Rejoinder
27. Least Squares Sparse Principal Component Analysis and Parallel Coordinates for Real-Time Process Monitoring
28. The Role of Big Data in Industrial (Bio)chemical Process Operations
29. Artificial Intelligence in Pharmacoepidemiology: A Systematic Review. Part 1—Overview of Knowledge Discovery Techniques in Artificial Intelligence
30. On monitoring industrial processes under feedback control
31. Experiences with big data: Accounts from a data scientist’s perspective
32. Quantifying the sources of uncertainty when calculating the limiting flux in secondary settling tanks using iCFD
33. A Comparative Study of Markov Decision Process Algorithms for Multi-component Condition-based Maintenance
34. Outliers detection using an iterative strategy for semi‐supervised learning
35. The revised Tennessee Eastman process simulator as testbed for SPC and DoE methods
36. Discussion on “Søren Bisgaard’s contributions to Quality Engineering: Design of experiments”
37. Monitoring batch processes with dynamic time warping and k-nearest neighbours
38. Added Value of Individual Flexibility Profiles of Electric Vehicle Users For Ancillary Services
39. Harvest time prediction for batch processes
40. Big data analytics using semi-supervised learning methods
41. Simulating flood risk under non-stationary climate and urban development conditions – Experimental setup for multiple hazards and a variety of scenarios
42. Big data analytics for industrial process control
43. Selection of objective function for imbalanced classification: an industrial case study
44. Selecting local constraint for alignment of batch process data with dynamic time warping
45. On the structure of dynamic principal component analysis used in statistical process monitoring
46. Selection of non-zero loadings in sparse principal component analysis
47. Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control
48. Process Knowledge Discovery Using Sparse Principal Component Analysis
49. Trellis plots as visual aids for analyzing split plot experiments
50. Split-plot designs for multistage experimentation
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