**Neural Network: **

Neural network is an information processing system that is inspired by the way biological nervous systems such as brain process information. A neural network is composed of a large number of interconnected processing elements known as neurons which are used to solve problems. A neural network is an attempt to make a computer model of the human brain and neural networks are parallel computing devices. The simple diagram of the neural network is as shown below:

**Fuzzy Logic: **

The term fuzzy represents the things which are not clear. In the real world many times we find a situation where we can’t determine whether the state is true or false, their fuzzy logic provides very valuable flexibility for reasoning. In this way, we can consider the inaccuracies and uncertainties of any situation. The simple diagram of fuzzy logic is as shown below:

## Difference between Neural Network And Fuzzy Logic

Neural Network | Fuzzy Logic |
---|---|

This system can not easily modified. | This system can easily modified. |

It trains itself by learning from data set | Everything must be defined explicitly. |

It is complex than fuzzy logic. | It is simpler than neural network. |

It helps to perform predictions. | It helps to perform pattern recognition. |

Difficult to extract knowledge. | Knowledge can easily extracted. |

It based on learning. | It doesn’t base on learning. |

## Recommended Posts:

- Implementation of Artificial Neural Network for AND Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for OR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for NAND Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for NOR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for XOR Logic Gate with 2-bit Binary Input
- Implementation of Artificial Neural Network for XNOR Logic Gate with 2-bit Binary Input
- Neural Logic Reinforcement Learning - An Introduction
- Implementing Artificial Neural Network training process in Python
- Introduction to Convolution Neural Network
- Introduction to Artificial Neural Network | Set 2
- A single neuron neural network in Python
- Applying Convolutional Neural Network on mnist dataset
- Introduction to Recurrent Neural Network
- Importance of Convolutional Neural Network | ML
- Neural Network Advances
- ML - Neural Network Implementation in C++ From Scratch
- Choose optimal number of epochs to train a neural network in Keras
- Implementation of neural network from scratch using NumPy
- Deep Neural Network With L - Layers
- ANN - Implementation of Self Organizing Neural Network (SONN) from Scratch

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.