Fuzzy modeling of complex systems
International Journal of Approximate Reasoning
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
Application of evolving Takagi-Sugeno fuzzy model to nonlinear system identification
Applied Soft Computing
Application of MR damper in structural control using ANFIS method
Computers and Structures
Multiobjective identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Fuzzy Systems
Automatic Design of Hierarchical Takagi–Sugeno Type Fuzzy Systems Using Evolutionary Algorithms
IEEE Transactions on Fuzzy Systems
System identification of high impact resistant structures
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Hi-index | 12.05 |
This paper proposes a novel model for predicting complex behavior of smart pavements under a variety of environmental conditions. The mathematical model is developed through an adaptive neuro fuzzy inference system (ANFIS). To evaluate the effectiveness of the ANFIS model, the temperature fluctuations at different locations in smart pavement systems equipped with pipe network systems under solar radiations is investigated. To develop the smart pavement ANFIS model, various sets of input and output field experimental data are collected from large-scale experimental test beds. The solar radiation and the inlet water flow are used as input signals for training complex behavior of the smart pavement ANFIS model, while the temperature fluctuation of the smart pavement system is used for the output signal. The trained model is validated using 20 different data sets that are not used for the training process. It is demonstrated from the simulation that the ANFIS identification approach is effective in modeling complex behavior of the pavement-fluid system under a variety of environmental conditions. Comparison with high fidelity data proves the viability of the proposed approach in pavement health monitoring setting, as well as automatic control systems.