Engineering Applications of Neural Computing: A State-of-the-Art Survey
CONSTRUCTION ENGINEERING RESEARCH LAB (ARMY) CHAMPAIGN IL
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Neural computing, as a paradigm of knowledge representation and information processing, has attracted tremendous enthusiasm and research interest recently. With advancing sophistication, neural computing technology has been successfully tailored for a wide range of applications, including some engineering fields. With the development of hardware based neural networks and neural computing theory, neural networks potentially provide efficient tools for solving some difficult engineering problems related to U.S. Army Construction Engineering Research Laboratories USACERL research. This report reviews and describes different types of neural networks including feedforward, feedback, and recurrent networks, their learning algorithms and recent developments. The emphasis is on the most frequently used multilayer feedforward neural networks. Representative publications on neural network applications to engineering problems related andor of interest to research at USACERL, especially civil engineering problems, are also covered, and each modeling methodology identified. An extensive reference list is provided with each subject. The appendices list major technical journals dedicated to the theory and application of neural computing, some publicly available neural network simulators, and selected books and proceedings published on neural networks and genetic algorithms.
- Computer Systems