چکیده
مقدمه
روش شناسی پیشنهادی
آزمایش کنید
نتیجه
منابع
Abstract
Introduction
The Proposed Methodology
Experiment
Conclusion
References
چکیده
با افزایش تنوع الگوهای لباس و حجم فزاینده دادههای الگو، روشهای سنتی تجزیه و تحلیل دادهها دیگر نمیتوانند پاسخگوی نیازهای فعلی برای تحلیل الگوی لباس باشند. به منظور تجزیه و تحلیل جامع داده های سبک نسخه لباس، از یک الگوریتم خوشه بندی بر اساس عوامل محبوب برای تجزیه و تحلیل آن استفاده شده است. با طبقهبندی دادههای سبک نسخه لباس، ویژگیهای سبک لباس هر دسته تجزیه و تحلیل میشود و تفاوتهای بین نسخههای مختلف پیدا میشود. سپس با استفاده از الگوریتم درخت تصمیم می توان محبوبیت سبک های لباس را پیش بینی کرد و استفاده از تجزیه و تحلیل داده های کمکی محاسباتی می تواند مرجع تصمیم گیری برای تولید شرکت های نساجی و پوشاک باشد و دقت را تا 7.91 درصد افزایش دهد.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
With the increasing diversification of clothing patterns and the increasing amount of pattern data, traditional data analysis methods can no longer meet the current needs for clothing pattern analysis. In order to comprehensively analyze the clothing version style data, a clustering algorithm based on popular factors is used to analyze it. By classifying the clothing version style data, the clothing style characteristics of each category are analyzed, and the differences between the various versions are found. Then, the popularity of clothing styles can be predicted by applying decision tree algorithm, and the use of computational auxiliary data analysis can provide decision-making reference for textile and clothing enterprises' production, and the accuracy can be increased by 7.91%.
Introduction
While the clothing industry has its strong popularity, the length of its product supply chain is also worthy of attention. The current changes in the domestic market are reflected in all aspects, such as the influx of foreign brands, the new normal of the domestic economy, and the growing popularity of apparel online marketing. These are driving apparel companies to have to respond more quickly to fashion. At the same time, the fashion cycle is getting shorter and shorter, and the spread of fashion and fashion is also getting faster. These are also promoting new changes in the main body of clothing fashion trend forecasting institutions, forecasting methods and communication methods to varying degrees [1-6].
Conclusion
This article analyzes the clothing version based on popular factors. In the research on the fashion trend optimization model of clothing design elements, we learned that in the actual development of clothing silhouette, color, material three elements and other auxiliary elements design and changes Through the hierarchical analysis and combination of trends in each link, and in accordance with the general cultural direction and brand style of the actual clothing brand, in the process of combining modern science and technology, the trend optimization model of clothing design is scientifically supported by computer technology. Reasonable hierarchical management of design elements.