An identification algorithm for vibrating dynamic characterization by using artificial neural network is developed for multi-degree-of freedom systems. The over-fitting problem of classical back-propagation algorithm during neural network training is solved by using regularization procedure with regularized objective function. The practical application shows that the proposed training method is capable of enhancing the regularization procedure without getting stuck at these sub-optimal solutions, can be used to noisy data in order to omit an over-fitted neural approximation and has higher identification accuracy compared to the back-propagation algorithm Key words: Neural network, Parameter identification, Regularization procedure, Vibratio...
For modelling a dynamic system in practice, it often faces the difficulty in improving the accuracy ...
The focus of this work is on the development and utilization of artificial neural networks (ANNs) fo...
In this study, a new approach is proposed for identification of structural nonlinearities by employi...
金沢大学理工研究域機械工学系This paper describes a convenient method of identification of nonlinear vibration syst...
Artificial Neural Network and Time Series Analysis are two emerging technologies. Neural Networks pr...
Artificial neural networks have gained increasing popularity in control area in recent years. This p...
The efficient characterization of nonlinear systems is an important goal of vibration and model test...
A novel neural network-based strategy is proposed and developed for the direct identification of str...
This work studies the capability of generalization of Neural Network using vibration based measureme...
Active control solutions may be preferable to passive solutions when size or weight become a constra...
A neural network-based approach is presented for the detection of changes in the characteristics of ...
A novel neural networks based strategy is proposed and developed for the direct identification of st...
International audienceNeural networks are applied to the identification of non-linear structural dyn...
Dynamic neural networks (DNNs), which are also known as recurrent neural networks, are often used fo...
The parameter identification using artificial neural networks is becoming very popular. In this chap...
For modelling a dynamic system in practice, it often faces the difficulty in improving the accuracy ...
The focus of this work is on the development and utilization of artificial neural networks (ANNs) fo...
In this study, a new approach is proposed for identification of structural nonlinearities by employi...
金沢大学理工研究域機械工学系This paper describes a convenient method of identification of nonlinear vibration syst...
Artificial Neural Network and Time Series Analysis are two emerging technologies. Neural Networks pr...
Artificial neural networks have gained increasing popularity in control area in recent years. This p...
The efficient characterization of nonlinear systems is an important goal of vibration and model test...
A novel neural network-based strategy is proposed and developed for the direct identification of str...
This work studies the capability of generalization of Neural Network using vibration based measureme...
Active control solutions may be preferable to passive solutions when size or weight become a constra...
A neural network-based approach is presented for the detection of changes in the characteristics of ...
A novel neural networks based strategy is proposed and developed for the direct identification of st...
International audienceNeural networks are applied to the identification of non-linear structural dyn...
Dynamic neural networks (DNNs), which are also known as recurrent neural networks, are often used fo...
The parameter identification using artificial neural networks is becoming very popular. In this chap...
For modelling a dynamic system in practice, it often faces the difficulty in improving the accuracy ...
The focus of this work is on the development and utilization of artificial neural networks (ANNs) fo...
In this study, a new approach is proposed for identification of structural nonlinearities by employi...