| LDR | | 03544cmm u22004937i 4500 |
| 001 | | 000000327753 |
| 003 | | OCoLC |
| 005 | | 20240307140458 |
| 006 | | m d |
| 007 | | cr cnu---unuuu |
| 008 | | 230616s2023 pau fob 001 0 eng d |
| 020 | |
▼a 1668456443
▼q electronic book |
| 020 | |
▼a 9781668456446
▼q (electronic bk.) |
| 020 | |
▼z 9781668456439
▼q hardcover |
| 024 | 7 |
▼a 10.4018/978-1-6684-5643-9
▼2 doi |
| 035 | |
▼a 3627440
▼b (N$T) |
| 035 | |
▼a (OCoLC)1382729915 |
| 040 | |
▼a IGIGL
▼b eng
▼e rda
▼c IGIGL
▼d OCLCF
▼d YDX
▼d N$T
▼d 248032 |
| 049 | |
▼a MAIN |
| 050 | 4 |
▼a TA347.A78
▼b A7935 2023 |
| 082 | 04 |
▼a 624.0285
▼2 23/eng/20220907 |
| 245 | 00 |
▼a Artificial Intelligence and machine learning techniques for civil engineering /
▼c Vagelis Plevris, Afaq Ahmad, and Nikos Lagaros, editors. |
| 264 | 1 |
▼a Hershey, Pennsylvania :
▼b IGI Global,
▼c [2023] |
| 300 | |
▼a 1 online resource (385 pages) |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 504 | |
▼a Includes bibliographical references and index. |
| 505 | 0 |
▼a Chapter 1. Artificial intelligence-assisted building information modelling -- Chapter 2. Deep learning-based damage inspection for concrete structures -- Chapter 3. Machine learning applications for vibration-based structural health monitoring -- Chapter 4. Use of AI and ML algorithms in developing closed-form formulae for structural engineering design -- Chapter 5. A predictive regression model for the shear strength of RC knee joint subjected to cyclic load -- Chapter 6. Predicting the fundamental period of light-frame wooden buildings by employing bat algorithm-based artificial neural network -- Chapter 7. Shear capacity of RC elements with transverse reinforcement through a variable-angle truss model with machine-learning-calibrated coefficients -- Chapter 8. Groundwater modelling of the saq aquifer using artificial intelligence and hydraulic simulations -- Chapter 9. Reliability analysis of RC code for predicting load-carrying capacity of RCC walls through ANN -- Chapter 10. The value proposition of machine learning in construction management: exploring the trends in construction 4.0 and beyond -- Chapter 11. Explainable safety risk management in construction with unsupervised learning -- Chapter 12. Enhanced stochastic paint optimizer for nonlinear Design of fuzzy logic controllers in steel building structures for the near-fault earthquakes. |
| 520 | 3 |
▼a "This reference book offers state-of-the-art contributions in the area of AI and its applications in the field of civil engineering presenting methods and implementation of AI and machine learning in multiple facets of civil engineering"--
▼c Provided by publisher. |
| 588 | |
▼a Description based on title screen (IGI Global, viewed 06/16/2023). |
| 590 | |
▼a Added to collection customer.56279.3 |
| 650 | 0 |
▼a Civil engineering
▼x Data processing. |
| 650 | 0 |
▼a Artificial intelligence. |
| 650 | 0 |
▼a Machine learning. |
| 650 | 7 |
▼a Artificial intelligence.
▼2 fast
▼0 (OCoLC)fst00817247 |
| 650 | 7 |
▼a Civil engineering
▼x Data processing.
▼2 fast
▼0 (OCoLC)fst00862494 |
| 650 | 7 |
▼a Machine learning.
▼2 fast
▼0 (OCoLC)fst01004795 |
| 700 | 1 |
▼a Plevris, Vagelis,
▼d 1976-,
▼e editor. |
| 710 | 2 |
▼a IGI Global,
▼e publisher. |
| 776 | 08 |
▼i Print version:
▼z 1668456435
▼z 9781668456439
▼w (DLC) 2022033195 |
| 856 | 40 |
▼3 EBSCOhost
▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3627440 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 3627440 |
| 990 | |
▼a 관리자 |
| 994 | |
▼a 92
▼b N$T |