Abstract
Currently, artificial neural networks (ANN) are used to solve the following complex problems: pattern recognition, speech recognition, complex forecasts and others. The main applications of ANN are decision making, pattern recognition, optimization, forecasting, data analysis. This paper presents an overview of applications of ANN in construction industry, including energy efficiency and energy consumption, structural analysis, construction materials, smart city and BIM technologies, structural design and optimization, application forecasting, construction engineering and soil mechanics.
Highlights
The construction industry has a lot of separate automated solutions from the design process to logistics and planning, but often these information systems are incompatible with each other, which is a limitation for creating effective machine learning and artificial intelligence systems
The potential of solutions based on artificial intelligence can be realized only through the integration of all sources of heterogeneous data [1]
In 1949, neuropsychologist Donald Hebb published the book [3] in which the first working learning algorithm for artificial neural networks was proposed
Summary
The construction industry has a lot of separate automated solutions from the design process to logistics and planning, but often these information systems are incompatible with each other, which is a limitation for creating effective machine learning and artificial intelligence systems. In 1949, neuropsychologist Donald Hebb published the book [3] in which the first working learning algorithm for artificial neural networks was proposed. In 1969, a former fellow student of Rosenblatt Marvin Minsky and Seymour Papert published the book [5], in which they presented rigorous mathematical proof that the perceptron is not capable of learning in most interesting cases. Since 1985, John Hopfield has been offering the world his vision of the design and operation of a neural network that is capable of solving certain types of problems It is the work of John Hopfield that once again fuels the serious interest of the world community in artificial neural networks.
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