Bidirectional associative memories
IEEE Transactions on Systems, Man and Cybernetics
Adaptive pattern recognition and neural networks
Adaptive pattern recognition and neural networks
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Neurocomputing
A general framework for parallel distributed processing
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Learning and relearning in Boltzmann machines
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Genetic programming for prediction of water flow and transport of solids in a basin
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
| Hi-index | 0.00 |
The Chapter provides an introduction to the diverse range of alternative artificial neural networks (ANNs) currently available and the types of application they have been adopted for in civil and structural engineering. The presentation is made with reference to a classification and decomposition of the main features of ANNs. An introduction is first provided of the essential features of a typical ANN, and its mode of operation. A brief graphical interpretation is presented to illustrate how ANNs model data, and to help gain insight to their scope of application, merits and drawbacks. An identification is then made of the different types of processing that can be performed at the neuron level, the lowest level in an ANN. This is followed by an identification of the different ways in which neurons can be combined into an integral processing device capable of solving non-trivial problems. The range of alternative function types that can be implemented by ANNs are then examined. Finally, a review is provided of the primary methods of developing/training ANNs to solve specific problems. At each stage in the chapter, relevant neural paradigms are referenced and areas of application in civil and structural engineering are identified.