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RISS 인기검색어
- 검색키워드
- 저자 : Subrata Sengupta (검색결과 2 건)
- 무료
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Partha Sengupta,Subrata Chakraborty 국제구조공학회 2022 Structural Engineering and Mechanics, An Int'l Jou Vol.81 No.1
The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.
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Parts of Speech and Sentence Type Determination based on Sentence Structure
Pranab Kumar Dhar,Subrata Sengupta,Jong-Myon Kim(김종면) 한국정보과학회 2008 한국정보과학회 학술발표논문집 Vol.35 No.2
This paper presents a new approach for parts of speech determination based on sentence structure. This approach can be classified as a rule based model for parts of speech determination. This model forms the sentence structure of an input sentence. It determines both the validity of the sentence using a phrase structure grammar and the correct parts of speech of the word used in the sentence from the valid sentence structure. This paper also presents the sentence type determination based on the sense, function, and structure formation of a sentence.
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