What is meant by soft computing?

Soft computing is defined as a group of computational techniques based on artificial intelligence (human like decision) and natural selection that provides quick and cost effective solution to very complex problems for which analytical (hard computing) formulations do not exist.

What is soft computing and its types?

Soft computing is the reverse of hard (conventional) computing. It refers to a group of computational techniques that are based on artificial intelligence (AI) and natural selection. It provides cost-effective solutions to the complex real-life problems for which hard computing solution does not exist.

What is Introduction to soft computing?

Soft computing (SC) is a branch, in which, it is tried to build intelligent and wiser machines. Soft computing is an emerging collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty, and partial truth to achieve robustness, tractability and total low cost.

What are types of soft computing?

There are of two types ANN (Artificial Neural Network) and BNN (Biological Neural Network). A neural network that processes a single element is known as a unit. The components of the unit are, input, weight, processing element, output.

What is soft computing example?

Soft computing is based on natural as well as artificial ideas. Soft Computing techniques are Fuzzy Logic, Neural Network, Support Vector Machines, Evolutionary Computation and Machine Learning and Probabilistic Reasoning. The present paper shows the techniques, applications and future of soft computing.

What is soft computing explain with example?

Soft computing is the use of approximate calculations to provide imprecise but usable solutions to complex computational problems. The tolerance of soft computing allows researchers to approach some problems that traditional computing can’t process. Soft computing uses component fields of study in: Fuzzy logic.

How does soft computing work?

Soft computing is the process of solving real-life complex problems using approximate calculations and gives solutions that are not very specific in nature just like the human brain works, which, unlike traditional computing, focuses on impartial truths and approximates.

What is the goal of soft computing?

GOALS OF SOFT COMPUTINGThe main goal of soft computing is to develop intelligent machines to provide solutions to real world problems, which are not modeled, or too difficult to model mathematically.

What are the requirements of soft computing?

Soft computing is based on natural as well as artificial ideas. Soft Computing techniques are Fuzzy Logic, Neural Network, Support Vector Machines, Evolutionary Computation and Machine Learning and Probabilistic Reasoning.

Where is soft computing used?

Soft Computing techniques are used by various medical applications such as Medical Image Registration Using Genetic Algorithm, Machine Learning techniques to solve prognostic problems in medical domain, Artificial Neural Networks in diagnosing cancer and Fuzzy Logic in various diseases [15].

What are the main advantages of soft computing?

The applications of soft computing approach have proved two main advantages:(1) it made solving nonlinear problems, in which mathematical models are not available, possible and (2) it introduced the human knowledge such as cognition, recognition, understanding, learning, and others into the fields of computing.

What are the advantages and disadvantages of soft computing?

While soft computing is tolerant of imprecision and uncertainty, hard computing requires precise state analytical model. Soft computing uses approximation, while hard computing needs precision. Soft-computing algorithms are capable of improving themselves and are self-evolving.

Which is the best introduction to soft computing?

Introduction to Soft Computing, topics : Definitions, goals, and importance. Fuzzy computing : classical set theory, crisp & non-crisp set, capturing uncertainty, definition of fuzzy set, graphic interpretations of fuzzy set – small, prime numbers, universal space, empty.

How many hours are there in soft computing?

The Course on Soft Computing refers to the odd semester (July–Nov) course, title Soft Computing, Code 07B71CI4-0-8, 4 Credits, Lectures – 42 hours, I offered to the students of 7th semester B.Tech course in the year, 2007, 2008, 2009, 2010, 2011, and 2012. The lecture slides, around 398 numbers in pdf format, have gone through three updates.

When was soft computing defined as a field?

Springer-Verlag Germany/USA 1997.]. •Zadeh, defined Soft Computing into one multidisciplinary system as the fusion of the fields of Fuzzy Logic, Neuro-Computing, Evolutionary and Genetic Computing, and Probabilistic Computing.

How is soft computing different from hard computing?

Soft computing differs from hard (conventional) computing. Unlike hard computing, the soft computing is tolerant of imprecision, uncertainty, partial truth, and approximation. The guiding principle of soft computing is to exploit these tolerance to achieve tractability, robustness and low solution cost.