Title: Optimisation strategy for ceramic cultural and creative product design combining analytic hierarchy process and AlexNet

Authors: Cong Wang; Qian Dong; Liangliang Lin

Addresses: School of English Language and Culture, Xi'an Fanyi University, Xi'an, 710105, Shaanxi, China ' School of Art and Design, Xi'an Fanyi University, Xi'an, 710105, Shaanxi, China ' Dance Academy, Xian Conservatory of Music, Xi'an, 710061, Shaanxi, China

Abstract: This study combines the analytic hierarchy process (AHP) and the AlexNet deep learning model to propose an optimisation strategy for ceramic cultural and creative product design. AlexNet extracts colour, texture, shape, and pattern features from six popular ceramic types, which are then reduced in dimensionality. Experts provide initial scores, and AHP calculates weights for the four evaluation criteria. Results show modern ceramic art achieves the highest comprehensive score of 5.078, with process difficulty having the highest weight at 0.279. This evaluation method offers a scientific reference for designers to enhance styles and optimise strategies.

Keywords: ceramic design; AlexNet algorithm; analytic hierarchy process; AHP; confusion matrix; feature extraction.

DOI: 10.1504/IJART.2025.150035

International Journal of Arts and Technology, 2025 Vol.15 No.4, pp.325 - 342

Received: 05 Mar 2025
Accepted: 17 May 2025
Published online: 21 Nov 2025 *

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