PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK
Indonesia use Bridge Management System (BMS) methodfor bridge monitoring and inspection system. This method still need development in accuracy and objectivity. In this paper, a stell truss bridge upper structure capacity prediction method using Artificial Neural Network (ANN) has been...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2014
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| author | , ANGGA TRISNA Y , Akhmad Aminullah, S.T., M.T., Ph.D. |
| author_facet | , ANGGA TRISNA Y , Akhmad Aminullah, S.T., M.T., Ph.D. |
| author_sort | , ANGGA TRISNA Y |
| collection | UGM |
| description | Indonesia use Bridge Management System (BMS) methodfor bridge monitoring
and inspection system. This method still need development in accuracy and
objectivity. In this paper, a stell truss bridge upper structure capacity prediction
method using Artificial Neural Network (ANN) has been proposed. Furthermpre,
this method may be advanced development of BMS method
ANN is a matematics modelling method for derivate an empirical equation to
solve an unique process from several unique input and output. Empirical equation
derivated from ANN has an high accuracy and proven by previous study. In this
case, empirical equation has derivated from input which describe bridge capacity
reduction factor and output which describe rating factor. Bridge capacity
reduction factor that has been proposed were age of bridge, actual maximum
load, actual yield stress, and element compactness. Study has implemented in
three bridge as case study, there were Lubuk Jambi Bridge, Kampar Kanan
Bridge, and Batang Nilau Bridge in Riau Province.
The study result indicated that empirical equation derivated from ANN for Lubuk
Jambi Bridge, Kampar Kanan Bridge, and Batang NilauBridge given good data
consistency and maximum error smaller than 10%, so the empirical equation has
been valid and accurate. Furthermore the empirical equation can be used to
predict capacity reduction for each bridge. |
| first_indexed | 2024-03-13T23:39:52Z |
| format | Thesis |
| id | oai:generic.eprints.org:133625 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:39:52Z |
| publishDate | 2014 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1336252016-03-04T07:52:14Z https://repository.ugm.ac.id/133625/ PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK , ANGGA TRISNA Y , Akhmad Aminullah, S.T., M.T., Ph.D. ETD Indonesia use Bridge Management System (BMS) methodfor bridge monitoring and inspection system. This method still need development in accuracy and objectivity. In this paper, a stell truss bridge upper structure capacity prediction method using Artificial Neural Network (ANN) has been proposed. Furthermpre, this method may be advanced development of BMS method ANN is a matematics modelling method for derivate an empirical equation to solve an unique process from several unique input and output. Empirical equation derivated from ANN has an high accuracy and proven by previous study. In this case, empirical equation has derivated from input which describe bridge capacity reduction factor and output which describe rating factor. Bridge capacity reduction factor that has been proposed were age of bridge, actual maximum load, actual yield stress, and element compactness. Study has implemented in three bridge as case study, there were Lubuk Jambi Bridge, Kampar Kanan Bridge, and Batang Nilau Bridge in Riau Province. The study result indicated that empirical equation derivated from ANN for Lubuk Jambi Bridge, Kampar Kanan Bridge, and Batang NilauBridge given good data consistency and maximum error smaller than 10%, so the empirical equation has been valid and accurate. Furthermore the empirical equation can be used to predict capacity reduction for each bridge. [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , ANGGA TRISNA Y and , Akhmad Aminullah, S.T., M.T., Ph.D. (2014) PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK. UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=74346 |
| spellingShingle | ETD , ANGGA TRISNA Y , Akhmad Aminullah, S.T., M.T., Ph.D. PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title | PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title_full | PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title_fullStr | PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title_full_unstemmed | PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title_short | PREDIKSI PENURUNAN KAPASITAS STRUKTUR ATAS JEMBATAN RANGKA BAJA DENGAN METODE ARTIFICIAL NEURAL NETWORK |
| title_sort | prediksi penurunan kapasitas struktur atas jembatan rangka baja dengan metode artificial neural network |
| topic | ETD |
| work_keys_str_mv | AT anggatrisnay prediksipenurunankapasitasstrukturatasjembatanrangkabajadenganmetodeartificialneuralnetwork AT akhmadaminullahstmtphd prediksipenurunankapasitasstrukturatasjembatanrangkabajadenganmetodeartificialneuralnetwork |