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Artificial Intelligence for Big Data

You're reading from  Artificial Intelligence for Big Data

Product type Book
Published in May 2018
Publisher Packt
ISBN-13 9781788472173
Pages 384 pages
Edition 1st Edition
Languages
Authors (2):
Anand Deshpande Anand Deshpande
Profile icon Anand Deshpande
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (19) Chapters close

Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
1. Big Data and Artificial Intelligence Systems 2. Ontology for Big Data 3. Learning from Big Data 4. Neural Network for Big Data 5. Deep Big Data Analytics 6. Natural Language Processing 7. Fuzzy Systems 8. Genetic Programming 9. Swarm Intelligence 10. Reinforcement Learning 11. Cyber Security 12. Cognitive Computing 1. Other Books You May Enjoy Index

ANFIS network


In earlier chapters, we saw the theory and practical applications of ANNs. When we combine the general theory of ANNs with fuzzy logic, we are able to get a neuro-fuzzy system that is a very efficient and powerful mechanism for modeling the real world input into intelligent machines, and producing output that are based on the adaptive judgement of a machine. This brings the computational frameworks very close to how a human brain would interpret the information and is able to take action within split seconds. Fuzzy logic itself has the ability to interpenetrate between human and machine interpretations of the data, information, and knowledge. However, it does not have an inherent capability to translate and model the process of transformation of human thought processes into rule based, self-learning, fuzzy inference systems (FIS).

ANNs can be utilized for automatically adjusting the membership functions based on the environmental context and training the network interactively...

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