Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy systems for diagnosis
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Can System Engineering: From Theory to Practical Applications
Can System Engineering: From Theory to Practical Applications
Neuro-fuzzy networks and their application to fault detection of dynamical systems
Engineering Applications of Artificial Intelligence
Document page segmentation using neuro-fuzzy approach
Applied Soft Computing
A novel approach for ANFIS modelling based on full factorial design
Applied Soft Computing
Modeling and simulation of combinational CMOS logic circuits by ANFIS
Microelectronics Journal
Predicting weather events using fuzzy rule based system
Applied Soft Computing
Fuzzy neural networks for water level and discharge forecasting with uncertainty
Environmental Modelling & Software
Expert Systems with Applications: An International Journal
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This paper presents an application of an Adaptive-Network-based Fuzzy Inference System (ANFIS) for pre-diagnosing incipient underlying in-vehicle network problems which possibly could cause further failures. An experiment on ANFIS-based pre-diagnosis of network level faults on Controller Area Network (CAN) by utilising available network protocol signals, such as error frames, is reported. The experimental results show that the pre-diagnostic system can efficiently classify causes of error frames transmitted on a CAN bus, and identify ''network health'' which indicates healthiness of the network when being used for message communication. The potential causes of the faults can be narrowed down, and further network diagnostics and prognostics can be performed.