By Topic

A Novel BP Algorithm Based on Three-term and Application in Service Selection of Ubiquitous Computing

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Haibin Cai ; Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai ; Daoqing Sun ; Qiying Cao ; Fang Pu

The standard back-propagation(BP) algorithm converges slowly and is easy to trap into local minimum, which are the main reasons why it cannot be used widely in real-time applications. Therefore, a novel BP algorithm based on three-term method consisting of a learning rate (LR), a momentum factor (MF) and a proportional factor (PF), called the TTMBP algorithm, was put forward in this paper. The convergence speed and stability were enhanced by adding PF. The self-adapting learning and self-adjusting-architecture methods are adopted in order that a moderate size networks model can be obtained according to environmental requirements. The novel BP algorithm is proposed to solve the problem of service selection in ubiquitous computing. We have fulfilled simulation in an actual power supply system for communication devices and the results of simulation show that the proposed control scheme is not only scalable but also efficient. The control scheme based on novel BP algorithm superior to the traditional service selection method based on trust mechanism. It can exactly choose a most suitable service from many target services and give the most perfect service performance to users

Published in:

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Date of Conference:

5-8 Dec. 2006