Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72775
Title: Neural network approach to seismic signal analysis
Authors: Wei, Foo Say 
Yee, Lin Ming
Issue Date: 1994
Source: Wei, Foo Say,Yee, Lin Ming (1994). Neural network approach to seismic signal analysis. Singapore ICCS - Conference Proceedings 1 : 215-219. ScholarBank@NUS Repository.
Abstract: This paper summarizes the preliminary findings of a Neural Network approach to automatic classification of moving objects based on seismic signals detected through a geophone. Four types of moving objects were considered: human beings, motorycles, cars and buses. A 32-16-4 network structure was used and the data was preprocessed before neural analysis. The results reveal 92% accuracy in classifying human beings from vehicles. However, only 74% accuracy was achieved in classifying the four different types of moving objects.
Source Title: Singapore ICCS - Conference Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/72775
Appears in Collections:Staff Publications

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