
 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 
