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020 _a9789811987908
024 7 _a10.1007/978-981-19-8790-8
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aTJ163.12
_b2023 EB
245 0 0 _aArtificial Intelligence in Mechatronics and Civil Engineering :
_bBridging the Gap
_cedited by Ehsan Momeni, Danial Jahed Armaghani, Aydin Azizi
250 _a1st ed 2023
264 1 _aSingapore
_bSpringer Nature
_c2023
300 _a1 recurso en línea
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 0 _aEmerging Trends in Mechatronics
_x2731-4863
505 0 _a1. Optical resistance switch for optical sensing -- 2. Empirical, statistical, and machine learning techniques for predicting surface settlement induced by Tunnelling -- 3. A review on the feasibility of Artificial Intelligence in Mechatronics -- 4. Feasibility of artificial intelligence techniques in rock characterization -- 5. A review on the application of soft computing techniques in Foundation Engineering.
520 _aRecent studies highlight the application of artificial intelligence, machine learning, and simulation techniques in engineering. This book covers the successful implementation of different intelligent techniques in various areas of engineering focusing on common areas between mechatronics and civil engineering. The power of artificial intelligence and machine learning techniques in solving some examples of real-life problems in engineering is highlighted in this book. The implementation process to design the optimum intelligent models is discussed in this book.
988 _aSpringer_Computer_2023
650 7 _2embne
_9496877
_aMecatrónica
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-8790-8
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b01/2024
_dz
_eb
_zSI