The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Fundamental Categories of Artificial Neural Networks
Abstract
The new era of the world uses artificial intelligence (AI) and machine learning. The combination of AI and machine learning is called artificial neural network (ANN). Artificial neural network can be used as hardware or software-based components. Different topology and learning algorithms are used in artificial neural networks. Artificial neural network works similarly to the functionality of the human nervous system. ANN is working as a nonlinear computing model based on activities performed by human brain such as classification, prediction, decision making, visualization just by considering previous experience. ANN is used to solve complex, hard-to-manage problems by accruing knowledge about the environment. There are different types of artificial neural networks available in machine learning. All types of artificial neural networks work based of mathematical operation and require a set of parameters to get results. This chapter gives overview on the various types of neural networks like feed forward, recurrent, feedback, classification-predication.
Related Content
|
Arunaben Prahladbhai Gurjar, Shitalben Bhagubhai Patel.
© 2022.
30 pages.
|
|
Meghna Babubhai Patel, Jagruti N. Patel, Upasana M. Bhilota.
© 2022.
10 pages.
|
|
Vo Ngoc Phu, Vo Thi Ngoc Tran.
© 2022.
27 pages.
|
|
Steven Walczak.
© 2022.
17 pages.
|
|
Priyanka P. Patel, Amit R. Thakkar.
© 2022.
26 pages.
|
|
Vo Ngoc Phu, Vo Thi Ngoc Tran.
© 2022.
34 pages.
|
|
Sarat Chandra Nayak, Subhranginee Das, Bijan Bihari Misra.
© 2022.
20 pages.
|
|
|