Multilayer feedforward networks are universal approximators
Neural Networks
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Extracting 3D Vortices in Turbulent Fluid Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data mining solutions: methods and tools for solving real-world problems
Data mining solutions: methods and tools for solving real-world problems
Data mining: building competitive advantage
Data mining: building competitive advantage
Mastering Data Mining: The Art and Science of Customer Relationship Management
Mastering Data Mining: The Art and Science of Customer Relationship Management
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
Acquisition of Symbolic Description from Flow Fields: A New Approach Based on a Fluid Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of artificial neural network in countercurrent spray saturator
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
| Hi-index | 0.01 |
This paper presents results from several analytical and empirical combustion process investigations using data mining tools and techniques. An artificial neural network was used to analyze the performance of data in phase Doppler anemometry (PDA) and particle image velocimetry (PIV) which can measure droplet size and velocity in combustion spray. The dataset used for the analysis was obtained from measurements in a practical combustion burner. The preliminary results are discussed, and improvements to the neural network architecture are suggested. The inclusion of additional input variables and modified data pre-processing improved the results of the classification process, providing a higher level of accuracy and narrower ranges of classified droplet sizes.