Journal ArticleDOI
Neural Networks in Civil Engineering: 1989–2000
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TLDR
Recent works on integration of neural networks with other computing paradigms such as genetic algorithm, fuzzy logic, and wavelet to enhance the performance of neural network models are presented.Abstract:
The first journal article on neural network application in civil/structural engineering was published by in this journal in 1989. This article reviews neural network articles published in archival research journals since then. The emphasis of the review is on the two fields of structural engineering and construction engineering and management. Neural networks articles published in other civil engineering areas are also reviewed, including environmental and water resources engineering, traffic engineering, highway engineering, and geotechnical engineering. The great majority of civil engineering applications of neural networks are based on the simple backpropagation algorithm. Applications of other recent, more powerful and efficient neural networks models are also reviewed. Recent works on integration of neural networks with other computing paradigms such as genetic algorithm, fuzzy logic, and wavelet to enhance the performance of neural network models are presented.read more
Citations
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Journal ArticleDOI
Short-term traffic forecasting: Where we are and where we’re going
TL;DR: In this article, the authors present a review of the existing literature on short-term traffic forecasting and offer suggestions for future work, focusing on 10 challenging, yet relatively under researched, directions.
Journal ArticleDOI
Steels for bearings
TL;DR: In this paper, the structure and properties of bearing steels prior to the point of service are first assessed and described in the context of steelmaking, manufacturing and engineering requirements, followed by a thorough critique of the damage mechanisms that operate during service and in accelerated tests.
Journal ArticleDOI
Spiking neural networks.
TL;DR: A state-of-the-art review of the development of spiking neurons and SNNs is presented, and insight into their evolution as the third generation neural networks is provided.
Journal ArticleDOI
Road Damage Detection Using Deep Neural Networks with Images Captured Through a Smartphone.
TL;DR: For the first time, a large-scale road damage dataset is prepared and it is demonstrated that the type of damage can be classified into eight types with high accuracy by applying the proposed object detection method.
Journal ArticleDOI
Improved spiking neural networks for EEG classification and epilepsy and seizure detection
TL;DR: It is concluded that RProp is the best training algorithm because it has the highest classification accuracy among all training algorithms specially for large size training datasets with about the same computational efficiency provided by SpikeProp.
References
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Optimization by Simulated Annealing
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Book ChapterDOI
Learning internal representations by error propagation
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Neural networks and physical systems with emergent collective computational abilities
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Learning internal representations by error propagation
TL;DR: In this paper, the problem of the generalized delta rule is discussed and the Generalized Delta Rule is applied to the simulation results of simulation results in terms of the generalized delta rule.
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Fuzzy sets as a basis for a theory of possibility
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