He worked in real-time systems, soft computing, and embedded computing in Mitsubishi Electric Research Labs.

In effect, the role model for soft computing is the human mind.

There is a main difference between soft computing and possibility.

Possibility is used when we don't have enough information to solve a problem but soft computing is used when we don't have enough information about the problem itself.

Components of soft computing include:

Another common contrast comes from the observation that inductive reasoning plays a larger role in soft computing than in hard computing.

He is a computer scientist with an international reputation on fuzzy neural network, soft computing, and machine intelligence.

His areas of research interests include fuzzy sets and uncertainty analysis, artificial neural networks for machine intelligence, pattern recognition, image processing, data mining, genetic algorithms, rough sets, and soft computing.

More current research since the 1990s include the areas of intelligent systems, generalized information theory, fuzzy set theory and fuzzy logic, theory of generalized measures, and soft computing.

Analyzing biological data may involve algorithms in artificial intelligence, soft computing, data mining, image processing, and simulation.