Soft Schemes for Earthquake-Geotechnical Dilemmas

Table 1

Central characteristics of soft computing technologies.

	Fuzzy sets	Artificial neural networks	Evolutionary computing, GA	Probabilistic reasoning	Chaotic computing
Weaknesses	(i) Knowledge acquisition; (ii) Learning	Black box interpretability	(i) Coding; (ii) Computational; speed	(i) Limitation of the axioms of probability theory; (ii) Lack of complete knowledge; (iii) Computational complexity	(i) Computational complexity; (ii) Chaos identification complexity
Strengths	(i) Interpretability; (ii) Transparency; (iii) Plausibility; (iv) Graduality; (v) Modeling; (vi) Reasoning; (vii) Tolerance to imprecision	(i) Learning; (ii) Adaptation; (iii) Fault tolerance; (iv) Curve fitting; (v) Generalization ability; (vi) Approximation ability	(i) Computational efficiency; (ii) Global optimization	(i) Rigorous framework; (ii) Good understanding	(i) Nonlinear dynamics simulation; (ii) Discovering chaos in observed data (with noise); (iii) Determining the predictability; (iv) Prediction strategies formulation