The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Artificial Higher Order Neural Network Nonlinear Models: SAS NLIN or HONNs?
Abstract
This chapter delivers general format of Higher Order Neural Networks (HONNs) for nonlinear data analysis and six different HONN models. This chapter mathematically proves that HONN models could converge and have mean squared errors close to zero. This chapter illustrates the learning algorithm with update formulas. HONN models are compared with SAS Nonlinear (NLIN) models and results show that HONN models are 3 to 12% better than SAS Nonlinear models. Moreover, this chapter shows how to use HONN models to find the best model, order and coefficients, without writing the regression expression, declaring parameter names, and supplying initial parameter values.
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.
|
|
|