Artificial neural networks and fuzzy neural networks for solving civil engineering problems

Abstract

[Excerpt] Based on the live cycle engineering aspects, such as prediction, design, assessment, maintenance, and management of structures, and according to performance-based approach, civil engineering structures have to fulfill essential requirements for resilience, sustainability, and safety from possible risks, such as earthquakes, fires, floods, extreme winds, and explosions.

The analysis of the performance indicators, which are of great importance for the structural behavior and for the fulfillment of the above-mentioned requirements, is impossible without conducting complex mathematical calculations. Artificial neural networks and Fuzzy neural networks are typical examples of a modern interdisciplinary field which gives the basic knowledge principles that could be used for solving many different and complex engineering problems which could not be solved otherwise (using traditional modeling and statistical methods). Neural networks are capable of collecting, memorizing, analyzing, and processing a large number of data gained from some experiments or numerical analyses. Because of that, neural networks are often better calculation and prediction methods compared to some of the classical and traditional calculation methods. They are excellent in predicting data, and they can be used for creating prognostic models that could solve various engineering problems and tasks. A trained neural network serves as an analytical tool for qualified prognoses of the results, for any input data which have not been included in the learning process of the network. Their usage is reasonably simple and easy, yet correct and precise. These positive effects completely justify their application, as prognostic models, in engineering researches.

The objective of this special issue was to highlight the possibilities of using artificial neural networks and fuzzy neural networks as effective and powerful tools for solving engineering problems. From 12 submissions, 6 papers are published. Each paper was reviewed by at least two reviewers and revised according to review comments. The papers covered a wide range of topics, such as assessment of the real estate market value; estimation of costs and duration of construction works as well as maintenance costs; and prediction of natural disasters, such as wind and fire, and prediction of damages to property and the environment. [...]