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Determination of neural network architecture for accident analysis | |
Author | Phusak Yuthayanont |
Call Number | AIT Thesis no. ST-98-46 |
Subject(s) | Neural networks (Computer science) Construction industry--Accidents |
Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Civil Engineering |
Publisher | Asian Institute of Technology |
Series Statement | Thesis ; no. ST-98-46 |
Abstract | This study presents the procedure and results of a system for construction accident analysis, which uses neural network techniques. The neural network recognizes the accident from the patterns of the historical records. In this study, simple characteristics were selected as the design factors affecting to the models. These characteristic factors were used as the input data to the neural network. The neural network learning procedure used a generalized delta rule, namely, a back-propagation algorithm. This approach makes use of the ability of learning, generalizing and nonlinear dynamic processing of neural network. The neural network can learn from a limited set of data. Therefore, this thesis proposes to implement neural network as an alternative solution to the stated problem. From the results of this application of a neural network, it was concluded that it would be possible to use the method to analyze accident in a construction site. |
Year | 1998 |
Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ST-98-46 |
Type | Thesis |
School | School of Civil Engineering |
Department | Other Field of Studies (No Department) |
Academic Program/FoS | Structural Engineering (STE) /Former Name = Structural Engineering and Construction (ST) |
Chairperson(s) | Minato, Takayuki |
Examination Committee(s) | Chotchai Charoenngam; Kazama, So |
Scholarship Donor(s) | Partial Scholarship |
Degree | Thesis (M.Eng.) - Asian Institute of Technology, 1998 |