Soft computing deals with imprecise or uncertain real-world problems using techniques like fuzzy logic, neural networks, genetic algorithms, and probabilistic reasoning. It aims to achieve tractability, robustness, and low solution cost for complex systems. Soft computing represents a paradigm shift from hard computing by reflecting the human ability to process imprecise information, and its techniques can evolve programs rather than requiring them to be written. The future impact of soft computing is expected to grow as its employment leads to systems with high machine intelligence.

1. Soft Computing

2.  Introduction
 What is Soft Computing?
 Soft Computing Tools
 Importance
 Future of Soft Computing
 Hard Computing Vs Soft Computing
 Conclusion

3.  More complex systems arising in biology, medicine, the
humanities, management sciences.
 Similar fields often remained intractable to conventional
mathematical and analytical methods
 Soft computing deals with imprecision, uncertainty, partial
truth, and approximation to achieve tractability, robustness
and low solution cost.

4.  It consists of distinct concepts and techniques which aim to
overcome the difficulties encountered in real world
problems.
 These problems result from the fact that our world seems to
be imprecise, uncertain and difficult to categorize.

5.  Fuzzy logic models
 Neural networks
 Genetic algorithms
 Machine Learning
 Probabilistic Reasoning

11.  The conceptual structure of soft computing suggests that
students should be trained not just in fuzzy logic,
neurocomputing, genetic programming, or probabilistic
reasoning but in all of the associated methodologies, though
not necessarily to the same degree.

12.  Soft computing represents a significant paradigm shift in the
aims of computing.
 A shift which reflects the fact that the human mind, unlike
present day computers, possesses a remarkable ability to
store and process information which is pervasively
imprecise,uncertain and lacking in categoricity.

13.  Hard computing based on binary logic, crisp systems,
numerical analysis and crisp software.
 Soft computing based on fuzzy logic, neural nets and
probabilistic reasoning.
 Hard computing requires programs to be written.
 Soft computing can evolve its own programs

14.  What is particularly significant is that in both consumer
products and industrial systems, the employment of soft
computing techniques leads to systems which have high MIQ
(Machine Intelligence Quotient).
 The successful applications of soft computing suggest that
the impact of soft computing will be felt increasingly in
coming years.