Genetic optimization for benefit-oriented data broadcast in T-learning

Chao-Chun Chen, Yong Ming Huang, Lien Fa Lin, Ding Chau Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Ubiquitous learning receives much attention in these few years due to its wide spectrum of applications, such as the T-learning application. The learner can use mobile devices to watch the digital TV based course content, and thus, the T-learning provides the ubiquitous learning environment. However, in real-world data broadcast environments, the mobile learners are unable to continuously watch a digital course for a long time, because the power of devices and the user patient constrain available learning time. In this paper, we design an optimal watching mode for data broadcast T-learning environment, such that the learner can retrieve as many distinct courses as possible within given time. We optimize the watching mode by using the genetic algorithm in order to reduce the computation cost of the optimization. Our experimental results show that genetic optimization process indeed reduces the computation cost, and still lead to a near optimal watching mode.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Pages403-408
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 1
Event8th International Conference on Intelligent Systems Design and Applications, ISDA 2008 - Kaohsiung, Taiwan
Duration: 2008 Nov 262008 Nov 28

Publication series

NameProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Volume1

Other

Other8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
CountryTaiwan
CityKaohsiung
Period08-11-2608-11-28

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'Genetic optimization for benefit-oriented data broadcast in T-learning'. Together they form a unique fingerprint.

Cite this