Soft computing techniques in structural and earthquake engineering: a literature review. (15th March 2020) - Falcone, Roberto; Lima, Carmine; Martinelli, Enzo
Highlights: This paper proposes a state-of-the-art review on the use of soft-computing techniques. Specifically, it considers the fields of structural and earthquake engineering. Fuzzy logic, Neural Networks and Evolutionary Computation techniques are mentioned. The latter, in turn, are categorised into Swarm Particle Intelligence and Genetic Algorithms. It is highlighted that soft-computing has not been employed so far in seismic retrofitting problems. Abstract: Although civil engineering problems are often characterized by significant levels of complexity, they are generally approached and solved by combining several practitioners' skills, such as intuition, past experience, logical reasoning, mathematical elaborations, and physical sense. This is also the case of problems in structural and earthquake engineering whose solution is generally based on the so-called "engineer's judgment". However, heuristic theories and algorithms within the framework of "soft computing" can provide a more rational and systematic way to approach and solve problems in these areas. As a matter of fact, the aforementioned algorithms have been recently utilized in several branches of engineering and applied sciences. This paper proposes a state-of-the-art review of the main applications of soft computing techniques to relevant structural and earthquake engineering problems. Specifically, the applications of fuzzy computing, evolutionary computing, swarm intelligence, and neural networks, as well as their hybrid combinations, are analyzed with the aim to examine their capability and limitations in modeling, simulation, and optimization problems.