4. SOFT COMPUTING
Soft computing can be traced back to the 1990s [8]. There are some early works such as a 1965 paper on fuzzy sets and a 1973 paper on complex system and decision processes by Lotfi Zadeh [8]. In 1994, the same author published the concept of soft computing [9]. Soft computing is related to techniques that attempt to imitate human abilities as a rationale for approximate answers rather than exact answers [8]. The main difference between conventional computing, called hard computing, and soft computing is that soft computing deals
particularly with imprecision, uncertainty and approximation, while hard computing underlies precision, certainty and exact solutions [8] . Generally, the three main areas in soft computing are fuzzy logic, neural networks and probabilistic reasoning [10]. Commonly, Bayesian networks and genetic algorithms are included in Probabilistic Reasoning [8].