Neural networks for optimal form design of personal digital assistants

Chen Cheng Wang; Yang Cheng Lin; Chung Hsing Yeh

doi:10.1007/978-3-642-02490-0_79

Neural networks for optimal form design of personal digital assistants

Chen Cheng Wang, Yang Cheng Lin, Chung Hsing Yeh

Department of Industrial Design

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

This paper presents a neural network (NN) approach to determining the optimal form design of personal digital assistants (PDAs) that best matches a given set of product images perceived by consumers. 32 representative PDAs and 9 design form elements of PDAs are identified as samples in an experimental study to illustrate how the approach works. Four NN models are built with different hidden neurons in order to examine how a particular combination of PDA form elements matches the desirable product images. The performance evaluation result shows that the number of hidden neurons has no significant effect on the predictive ability of the four NN models. The NN models can be used to construct a form design database for supporting form design decisions in a new PDA product development process.

Original language	English
Title of host publication	Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers
Pages	647-654
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-02490-0_79
Publication status	Published - 2009 Sept 21
Event	15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland, New Zealand Duration: 2008 Nov 25 → 2008 Nov 28

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	5506 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	15th International Conference on Neuro-Information Processing, ICONIP 2008
Country/Territory	New Zealand
City	Auckland
Period	08-11-25 → 08-11-28

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-02490-0_79

Cite this

Wang, C. C., Lin, Y. C., & Yeh, C. H. (2009). Neural networks for optimal form design of personal digital assistants. In Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers (PART 1 ed., pp. 647-654). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-02490-0_79

Wang, Chen Cheng ; Lin, Yang Cheng ; Yeh, Chung Hsing. / Neural networks for optimal form design of personal digital assistants. Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers. PART 1. ed. 2009. pp. 647-654 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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Wang, CC, Lin, YC & Yeh, CH 2009, Neural networks for optimal form design of personal digital assistants. in Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5506 LNCS, pp. 647-654, 15th International Conference on Neuro-Information Processing, ICONIP 2008, Auckland, New Zealand, 08-11-25. https://doi.org/10.1007/978-3-642-02490-0_79

Neural networks for optimal form design of personal digital assistants. / Wang, Chen Cheng; Lin, Yang Cheng; Yeh, Chung Hsing.
Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers. PART 1. ed. 2009. p. 647-654 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - This paper presents a neural network (NN) approach to determining the optimal form design of personal digital assistants (PDAs) that best matches a given set of product images perceived by consumers. 32 representative PDAs and 9 design form elements of PDAs are identified as samples in an experimental study to illustrate how the approach works. Four NN models are built with different hidden neurons in order to examine how a particular combination of PDA form elements matches the desirable product images. The performance evaluation result shows that the number of hidden neurons has no significant effect on the predictive ability of the four NN models. The NN models can be used to construct a form design database for supporting form design decisions in a new PDA product development process.

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Wang CC, Lin YC, Yeh CH. Neural networks for optimal form design of personal digital assistants. In Advances in Neuro-Information Processing - 15th International Conference, ICONIP 2008, Revised Selected Papers. PART 1 ed. 2009. p. 647-654. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-02490-0_79

Neural networks for optimal form design of personal digital assistants

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