Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy

Senbiao Liu, Yaohui Keane Liu, Kwan yu Chris Lo, Chi Wai Kan

Research output: Journal article publicationReview articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Based on a selection of 101 articles published from 2013 to 2022, this study systematically reviews the application of intelligent techniques and optimization algorithms in textile colour management. Specifically, the study explores how these techniques have been applied to four subfields within textile colour management: colour matching and prediction, colour difference detection and assessment, colour recognition and segmentation, and dye solution concentration and decolourization. Following an introduction to intelligent techniques and optimization algorithms in textile colour management, the study describes the specific applications of these techniques in the field over the past decade. Descriptive statistics are used to analyse trends in the use of these techniques and optimization algorithms, and comparative performances indicate the effectiveness of the techniques and algorithms. The study finds that the primary intelligent techniques used in the field of textile colour management include artificial neural networks (ANN), support vector machines (SVM) such as SVM, LSSVM, LSSVR, SLSSVR, FWSVR, fuzzy logic (FL) and adaptive neuro-fuzzy inference systems (ANFIS), clustering algorithms (e.g., K-means, FCM, X-means algorithms), and extreme learning machines (ELM) such as ELM, OSLEM, KELM, RELM. The main optimization algorithms used include response surface methodology (RSM), genetic algorithms (GA), particle swarm optimization (PSO), and differential evolution (DE). Finally, the study proposes a comparison of the performance of intelligent techniques and optimization algorithms, summarizes the relevant research trends, and suggests future research opportunities and directions, besides stating the limitations of this paper.

Original languageEnglish
Article number13
JournalFashion and Textiles
Volume11
Issue number1
DOIs
Publication statusPublished - Dec 2024

Keywords

  • Intelligent techniques
  • Optimisation algorithms
  • Performance comparison reference
  • Review
  • Textile colour management

ASJC Scopus subject areas

  • Social Psychology
  • Cultural Studies
  • Materials Science (miscellaneous)
  • Strategy and Management
  • Marketing

Fingerprint

Dive into the research topics of 'Intelligent techniques and optimization algorithms in textile colour management: a systematic review of applications and prediction accuracy'. Together they form a unique fingerprint.

Cite this