Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder /
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| Main Author: | |
|---|---|
| Format: | Thesis Book Chapter |
| Language: | English |
| Published: |
2020.
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| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/12466/ |
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| 001 | u1141688 | ||
| 003 | SIRSI | ||
| 005 | 202103050947 | ||
| 008 | 210305s2020 my a m 000 0 eng d | ||
| 040 | |a UMM |d AUM |e rda | ||
| 090 | |a TA145 |b UMP 2020 Gor | ||
| 097 | |a TA145 |b UMP 2020 Gor | ||
| 100 | 1 | |a Gordan, Meisam, |e author | |
| 245 | 1 | 0 | |a Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / |c Meisam Gordan. |
| 264 | 1 | |c 2020. | |
| 300 | |a xxiii, 198 leaves : |b illustrations (some colour) ; |c 30 cm | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 337 | |a computer |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 338 | |a computer disc |2 rdacarrier | ||
| 502 | |b Ph.D. |c Jabatan Kejuruteraan Awam, Fakulti Kejuruteraan, Universiti Malaya |d 2020. | ||
| 504 | |a Bibliography: leaves 161-190. | ||
| 530 | |a Also issued in CD. | ||
| 650 | 0 | |a Structural analysis (Engineering) |x Data processing. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Support vector machines. | |
| 710 | 2 | |a Universiti Malaya. |b Jabatan Kejuruteraan Awam, |e degree granting institution. | |
| 856 | 4 | 1 | |u http://studentsrepo.um.edu.my/12466/ |
| 900 | |a FNM NSM | ||
| 596 | |a 1 7 25 | ||
| 999 | |a TA145 UMP 2020 GOR |w LC |c 1 |i A517646741 |f 18/3/2021 |g 1 |l STACKS |m P01UTAMA |r Y |s Y |t TESIS |u 5/3/2021 |1 STEM | ||
| 999 | |a TA145 UMP 2020 GOR |w LC |c 1 |i A517646755 |f 26/3/2021 |g 1 |l STACKS |m P25UMARCHI |r N |s Y |t CD |u 26/3/2021 |1 STEM |o .STAFF. MST-CD627 | ||
| 999 | |a TA145 UMP 2020 GOR |w LC |c 1 |i A517692105 |f 28/3/2022 |g 1 |l STACKS |m P07JURUTER |r Y |s Y |t TESIS |u 28/3/2022 |1 STEM | ||