Improving the adaptive neuro-fuzzy method to intellectualize multisensor signals processing
- Resource Type
- Conference
- Authors
- Jun, Su; Roshchupkina, Nataliia; Roshchupkin, Oleksiy; Kochan, Volodymyr
- Source
- 2018 International Conference on Development and Application Systems (DAS) Development and Application Systems (DAS), 2018 International Conference on. :204-209 May, 2018
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
Robotics and Control Systems
Signal Processing and Analysis
Training
Adaptive systems
Artificial neural networks
Semiconductor device measurement
Fuzzy logic
Predictive models
multisensor
sensor
adaptive neuro-fuzzy inference system
individual conversion functions
- Language
This research paper presents an improved method and software implementation of intellectualization processing for multisensor signals by integrating the modified method of identifying individual conversion functions of multisensor and adaptive neuro-fuzzy inference system. The results of the training and data approximation of adaptive neuro-fuzzy inference system with noise amplitude of 2.5% in training vector for an advanced set of rebuilt points on the surface of the individual conversion function are obtained. The proposed algorithm provides high accuracy of training and approximation data and a low error of artificial neural network training.