Add to ORKGThe recent developments in multilayer perceptron using the backpropagation algorithm, has opened up new possibilities in structural identification. Limitation of traditional neural networks (TNN) in dealing with patterns that may vary in time domain has given birth to time-delay neural networks (TDNN). In the present paper the TNN and the TDNN have been implemented in detecting the damage in bridge structure using vibration signature analysis. A comparative study has been carried out for the various cases of complete as well as incomplete measurement data. It has been observed that TDNNs have performed better than Tows in this application
A novel neural networks based strategy is proposed and developed for the direct identification of st...
The shallow features extracted by the traditional artificial intelligence algorithm-based damage ide...
A method that uses machine learning to detect and localize damage in railway bridges under various e...
The recent developments in multilayer perceptron using the backpropagation algorithm, has opened up ...
A damage detection approach based on Artificial Neural Network (ANN), using the statistics of struct...
Damage detection by measurement of vibration signatures is highly attractive for monitoring bridges ...
Damage detection by measuring and analyzing vibration signals in a machine component is an establish...
Structural health monitoring is a challenging task that has recently received great attention from r...
Bridges are a crucial part of the transport infrastructure network, and their safety and operational...
The idea of using measured dynamic characteristics for damage detection is attractive because it all...
Recent developments in artificial neural networks (ANN) have opened up new possibilities in the doma...
This paper presents a review of the results of a structural health monitoring (SHM) study to track t...
This paper presents a review of the results of a structural health monitoring (SHM) study to track t...
This paper proposes the use of transmissibility functions combined with a machine learning algorithm...
This paper proposes the use of transmissibility functions combined with a machine learning algorithm...
A novel neural networks based strategy is proposed and developed for the direct identification of st...
The shallow features extracted by the traditional artificial intelligence algorithm-based damage ide...
A method that uses machine learning to detect and localize damage in railway bridges under various e...
The recent developments in multilayer perceptron using the backpropagation algorithm, has opened up ...
A damage detection approach based on Artificial Neural Network (ANN), using the statistics of struct...
Damage detection by measurement of vibration signatures is highly attractive for monitoring bridges ...
Damage detection by measuring and analyzing vibration signals in a machine component is an establish...
Structural health monitoring is a challenging task that has recently received great attention from r...
Bridges are a crucial part of the transport infrastructure network, and their safety and operational...
The idea of using measured dynamic characteristics for damage detection is attractive because it all...
Recent developments in artificial neural networks (ANN) have opened up new possibilities in the doma...
This paper presents a review of the results of a structural health monitoring (SHM) study to track t...
This paper presents a review of the results of a structural health monitoring (SHM) study to track t...
This paper proposes the use of transmissibility functions combined with a machine learning algorithm...
This paper proposes the use of transmissibility functions combined with a machine learning algorithm...
A novel neural networks based strategy is proposed and developed for the direct identification of st...
The shallow features extracted by the traditional artificial intelligence algorithm-based damage ide...
A method that uses machine learning to detect and localize damage in railway bridges under various e...