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題 名 | 以非線性迴歸法建立織物視覺質感之客觀評估模式=Using Nonlinear Regression to Establish Objective Evaluation Model for the Visual Texture of Fabrics |
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作 者 | 林宗煌; 賴顯松; | 書刊名 | 紡織綜合研究期刊 |
卷 期 | 17:2 2007.04[民96.04] |
頁 次 | 頁43-48 |
分類號 | 424.1 |
關鍵詞 | 織物視覺質感; 客觀評估; 襯衫布料; 非線性迴歸; Visual texture of fabrics; Shirts; Objective evaluation; Nonlinear; Regression method; |
語 文 | 中文(Chinese) |
中文摘要 | 本研究管在適用非線性迴歸法,建立客觀織物總實是之評估模式,盼望籍由織物「輕薄-厚重」、「細緻-粗獷」、「鮮明-暗淡」、「簡潔-繁雜」、及「涼爽-溫暖」等基本質感,去預測夏季男仕襯衫用布所須具備之總質感。由研究結果發現,確實可利用對數、倒數、二次曲線、三次曲線、混合、幕次、S、成長及指數等非線性迴歸法,建立織物視覺總感的預測模式。其判別係數依序分別為:0.6194、0.3832、0.7864、0.7885、0.7681、0.6517、0.4226、 0.7861及0.7681。除了倒數及S模式之擬合能力較差之外,其模7種模式,均有很好解釋能力。 |
英文摘要 | This study aims to use Nonlinear Regression Method to establish an objective evaluation model of fabric overall textures by means of the 5 primary textures, including “Thin – Thick” , “Cool - Warm” , “Exquisite – Wild” , “Bright – Dark” and “Simple – Complex” . The study results show that the prediction model of 9 overall fabric visual textures can in fact be established through Nonlinear Regression Methods, including corresponding number, inverse number, conic section, cubic section, mixing, power, S, growth and index. The discriminated coefficients of the 9 models are 0.6194, 0.3832, 0.7864, 0.7885, 0.7681, 0.6517, 0.4226, 0.7861 and 0.7681, respectively. Except inverse number and S, the remaining 7 models have good fitted ability. |
本系統中英文摘要資訊取自各篇刊載內容。