Akademik Veri Yönetim Sistemi
YOBU International middle anatolian symposium, Yozgat Bozok University(YOBU), , Yozgat, Türkiye, 16 - 18 Mayıs 2024, cilt.1, sa.1, ss.1-2
Civil
engineering mostly deals with technical issues in life cycle. It can be said
that information is a general name for systems that contain these life
experiences. In this regard, artificial intelligence (AI) is based on
mathematics and coding infrastructure, uses databases, and has many different
types of the experience databases to extract outputs for the systems. When we look at the content of AI, there is a
well-prepared, accurately measured and safe database, experience and code
support, and an expert person who integrates them with each other. Within this
sequence, AI can produce one or more solutions to any an experienced problem,
and it can also produce some outputs for problems that have not been
experienced before. At this point, the results of AI should be evaluated by an
expert in detail. However, risk and danger factors exist for both problem
solutions. Methods of AI have been extensively used in many scientific and
industrial areas such as computer science, robotics, engineering, medicine,
translation, economics, business, and psychology since 1950’s. Additionally,
there is also the field of architectural design within the solution methods of
AI. For example, it offers preliminary solutions for construction structures
such as building, bridge, stadium, road, dam, airport etc. Various studies in
the current literature show that the AI in modelling approaches have very close
results to the real measured data for solution of linear, non-linear, and other
systems. Results, especially those involving numerical variables, can also be
compared with classical methods in the literature. In this study, some
the current state-of-the-art and progress studies on the modelling of AI in civil
engineering were reviewed by using tables and graphics. Furthermore, some
future research possibilities and suggestions were given in the study.