2024 Vol.7 Aug.N04

• Title: Prediction method of color fashion trend of antique clothing in the era of big data
• Name: Yalin Jiao
• Company: International School/College of Pan-Chinese,Huaqiao University， Quanzhou 362021，China
• Abstract:

   Because of the complexity of hue components of ancient clothing colors, when predicting color fashion trends, there is usually a lack of effective analysis of hue characteristics, which leads to poor prediction results. In this regard, the prediction method of color fashion trend of antique clothing in the era of big data is proposed. Firstly, through the statistical analysis of the initial quantitative data of hue attributes of finalized colors from 2021 to 2023, the frequency distribution of different hue values is obtained, and the preliminary understanding of hue in color finalization is realized. Then, combined with the fuzzy C-means clustering algorithm, the color category clustering analysis is carried out, so that the color popular data is divided into several color categories. Finally, the generated color category labels are used as features, and the time stamps are converted into features that can be used in machine learning models. Combined with logistic regression models, a prediction model of color fashion trends is constructed. Finally, by constructing an experimental comparison link, the actual color trend prediction effect of this method is verified. Through the visual analysis of the results, it is clear that the consistency of color trends under the prediction results is obviously high, and it has an ideal prediction effect.

  
  

• Keyword: antique clothing; Color prediction; Logistic regression; Hue analysis;
• DOI: 10.12250/jpciams2024090805
• Citation form: Yalin Jiao.Prediction method of color fashion trend of antique clothing in the era of big data[J]. Computer Informatization and Mechanical System,2024,Vol.7,pp.17-20

[1] Park C W , Moon Y H , Eom I K .Image Tampering Localization Using Demosaicing Patterns and Singular Value Based Prediction Residue[J].IEEE Access, 2021, PP(99):1-1.

[2] Beyaz A , Koc D G .Meta-Learning-Based Prediction of Different Corn Cultivars from Color Feature Extraction[J].Tarim Bilimleri Dergisi, 2021, 27(1):32-41.

[3]Jagdeep-Singh,Varinderpal-Singh.Prediction of spring maize yields using leaf color chart, chlorophyll meter, and GreenSeeker optical sensor[J].Experimental Agriculture, 2021:1-12.

[4] Quesnel E , Poncet S , Altazin S , et al.Lifetime prediction of encapsulated CdSexS1-x quantum platelets for color conversion in high luminance LED microdisplays.[J].Optics express, 2023, 31 7:, 10955-10964.

[5] Beyaz A , Koc D .Meta-learning Based Prediction of Different Corn Cultivars from Colour Feature Extraction with Image Processing Technique[J].Journal of Agricultural Sciences, 2021, 27:32-41.

[6] Cui P , Xue Y , Liu Y , et al.Intelligent manufacturing of color blended yarn: Color matching algorithm and manufacturing process through computer numerically controlled ring  spinning system:[J].Journal of Engineered Fibers and Fabrics, 2021, 16:80-95.

[7] Yuan G , Wang Y , Peng J ,et al.A Novel Driving Behavior Learning and Visualization Method With Natural Gaze Prediction[J].IEEE Access, 2021, PP(99):1-1.

[8] Chaudhry M M A , Hasan M M , Erkinbaev C , et al.Bison muscle discrimination and color stability prediction using near-infrared hyperspectral imaging[J].Biosystems Engineering, 2021, 209:1-13. 

[9] Sun X , Xue Y , Xu Q ,et al.Research on colored yarns for a full color phase mixing model and the Stearns–Noechel color prediction approach[J].Textile Research Journal, 2022, 93:206 - 220.

[10] Gao Z , Zhang Y , Zhou S , et al.An enhanced quantum-inspired gravitational search algorithm for color prediction based on the absorption spectrum:[J].Textile Research Journal, 2021, 91(11-12):1211-1226.

[11] Jiang D, Li G, Sun Y,  et al. Manipulator grabbing position detection with information fusion of color image and depth image using deep learning[J] . Journal of Ambient Intelligence and Humanized Computing, 2021, 12: 10809-10822.

[12] Han A, Kim J, Ahn J. Color Trend Analysis using Machine Learning with Fashion Collection Images[J]. Clothing and Textiles Research Journal, 2022, 40(4): 308-324.

[13] Zhao L, Li M, Sun P. Neo-fashion: A data-driven fashion trend forecasting system using catwalk analysis[J]. Clothing and Textiles Research Journal, 2024, 42(1): 19-34.

[14] Shi M, Chussid C, Yang P, et al. The exploration of artificial intelligence application in fashion trend forecasting[J]. Textile Research Journal, 2021, 91(19-20): 2357-2386.

[15] Sharma S, Koehl L, Bruniaux P, et al. Development of an intelligent data-driven system to recommend personalized fashion design solutions[J]. Sensors, 2021, 21(12): 4239-4242.