What is hard computing?

1. Traditional computing techniques based on principles of precision, uncertainty and rigor. The problems based on analytical model can be easily solved using such techniques.

What is soft computing example?

Soft computing is the use of approximate calculations to provide imprecise but usable solutions to complex computational problems. Soft computing is sometimes referred to as computational intelligence. Soft computing provides an approach to problem-solving using means other than computers.

What is the example of hard computing?

Hard Computing Examples of conventional algorithms are merge sort, quick sort, binary search, greedy algorithm, dynamic programming etc which are deterministic.

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 Geeksforgeeks?

In the fields of Mechanical Engineering, soft computing is a role model for computing problems such that how a machine will works and how it will make the decision for a specific problem or input given.

What is soft computing Tutorialspoint?

Soft computing is a computing model evolved to solve non-linear issues. It helps to solve issues where human intelligence is needed to solve. Probabilistic models, fuzzy logic, neural networks, evolutionary algorithms are part of soft computing.

Where is hard computing used?

Applications of hard computing are mobile robot coordination and forecasting combinational problems. If we want to solve the deterministic problems, we can use a hard computing approach. As the problem grows in size and complexity, the design search space also increases.

Why do we use soft computing?

Soft computing helps users to solve real-world problems by providing approximate results that conventional and analytical models cannot solve. It is based on Fuzzy logic, genetic algorithms, machine learning, ANN, and expert systems.

What are types of soft computing?

Following are three types of techniques used by soft computing: Fuzzy Logic. Artificial Neural Network (ANN) Genetic Algorithms.

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].

Is AI and soft computing same?

A.I. Artificial Intelligence is the art and science of developing intelligent machines. Soft Computing aims to exploit tolerance for uncertainty, imprecision, and partial truth. AI plays a fundamental role in finding missing pieces between the interesting real world problems.

What is the aim of soft computing?

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. Soft computing methodologies have been advantageous in many applications.

What are the characteristics of soft and hard computing?

As against, approximation and dispositionality are the characteristics of soft computing. Soft computing approach is probabilistic in nature whereas hard computing is deterministic. Soft computing can be easily operated on the noisy and ambiguous data. In contrast, hard computing can work only on exact input data.

What is softsoft computing?

Soft Computing could be a computing model evolved to resolve the non-linear issues that involve unsure, imprecise and approximate solutions of a tangle. These sorts of issues square measure thought of as real-life issues wherever the human-like intelligence is needed to resolve it.

Is the soft computing model deterministic?

The answer could be yes or no, which means in two possible deterministic way we can answer the question or in other words, the answer contains a crisp or binary solution. The soft computing model is imprecision tolerant, partial truth, approximation.

What are real-life problems in soft computing?

These types of problems are considered as real-life problems where the human-like intelligence is required to solve it. The soft computing term is coined by Dr Lotfi Zadeh, according to him, soft computing is an approach which imitates the human mind to reason and learns in an environment of uncertainty and impression.

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