本文關(guān)鍵詞： 冷軋帶鋼 表面缺陷信息 內(nèi)容推薦 協(xié)同推薦 混合加權(quán)推薦　出處：《武漢科技大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：目前在冷軋帶鋼表面缺陷處理過程中,由于缺陷信息復(fù)雜多變且大都采用人工分析缺陷產(chǎn)生原因的方式,導(dǎo)致相關(guān)用戶實(shí)施整改措施滯后,產(chǎn)品缺陷影響持續(xù)擴(kuò)大。針對這一問題,本文結(jié)合當(dāng)代互聯(lián)網(wǎng)廣泛應(yīng)用的信息智能推薦方法,對冷軋帶鋼表面缺陷匹配信息推薦算法進(jìn)行了研究。根據(jù)帶鋼相關(guān)的缺陷信息、用戶信息和經(jīng)驗(yàn)信息的特點(diǎn),結(jié)合內(nèi)容過濾和協(xié)同過濾的優(yōu)勢,采用混合加權(quán)的方法,提出一種適用于帶鋼表面缺陷的混合推薦算法。通過帶鋼表面缺陷實(shí)例數(shù)據(jù)的分析驗(yàn)證表明,該混合推薦算法對比單一算法具有更高的準(zhǔn)確性和用戶接受度。本文主要的研究工作如下:(1)對冷軋帶鋼表面缺陷信息、用戶信息和經(jīng)驗(yàn)信息進(jìn)行分析和整理,全面總結(jié)信息數(shù)據(jù)的特點(diǎn),在基于專家經(jīng)驗(yàn)的基礎(chǔ)上建立經(jīng)驗(yàn)信息映射關(guān)系數(shù)據(jù)表,并根據(jù)冷軋帶鋼表面缺陷信息與用戶信息的關(guān)聯(lián)特點(diǎn),確立打分評價體系。(2)在滿足冷軋帶鋼表面缺陷匹配信息推薦系統(tǒng)對推薦算法的實(shí)際需求下,結(jié)合基于內(nèi)容過濾算法和協(xié)同過濾算法各自的優(yōu)點(diǎn),采用混合加權(quán)的方法,設(shè)計一種應(yīng)用于冷軋帶鋼表面缺陷匹配信息的混合加權(quán)推薦算法,其中采用夾角余弦相似度方法作為文本推薦算法,基于貝葉斯網(wǎng)絡(luò)模型法作為協(xié)同過濾推薦的算法。(3)根據(jù)冷軋帶鋼產(chǎn)線實(shí)際情況,對其表面缺陷信息進(jìn)行推薦算法的驗(yàn)證研究。案例中確定混合加權(quán)推薦算法的權(quán)重系數(shù)等值,分別計算得出基于內(nèi)容推薦算法、基于協(xié)同推薦算法和混合加權(quán)推薦算法的推薦結(jié)果,并從推薦結(jié)果、推薦精度、用戶接受度等方面對算法進(jìn)行分析比較。最后設(shè)計冷軋帶鋼表面缺陷匹配信息推薦算法的三個主要軟件功能模塊:缺陷匹配信息推薦模塊、打分?jǐn)?shù)據(jù)庫模塊和文本內(nèi)容信息庫模塊,并通過Visual Studio 2013軟件開發(fā)平臺實(shí)現(xiàn)冷軋帶鋼表面缺陷匹配信息推薦算法的功能。
[Abstract]:At present, in the process of surface defect treatment of cold-rolled strip, due to the complex and changeable defect information and the manual analysis of the causes of defects, the relevant users are lagging behind in the implementation of corrective measures. The influence of product defects continues to expand. In view of this problem, combining with the information intelligent recommendation method widely used in contemporary Internet, this paper studies the recommendation algorithm of surface defect matching information for cold-rolled strip steel, and according to the defect information related to strip steel, The characteristics of user information and experience information, combined with the advantages of content filtering and collaborative filtering, are combined with the method of mixed weighting. A hybrid recommendation algorithm for surface defects of steel strip is proposed. Compared with the single algorithm, the hybrid recommendation algorithm has higher accuracy and user acceptance. The main research work of this paper is as follows: 1) the surface defect information, user information and experience information of cold rolled strip are analyzed and sorted out. The characteristics of information data are summarized in an all-round way. Based on the expert experience, the relational data table of empirical information mapping is established, and according to the characteristics of the correlation between the surface defect information of cold rolled strip and user information, In order to meet the actual requirement of the recommendation system for the surface defect matching information of cold-rolled strip, combining the advantages of the content-based filtering algorithm and the cooperative filtering algorithm, the mixed weighted method is adopted. A hybrid weighted recommendation algorithm applied to the surface defect matching information of cold-rolled strip is designed, in which the angle cosine similarity method is used as the text recommendation algorithm. Based on Bayesian network model method as a collaborative filtering recommendation algorithm, according to the actual situation of cold-rolled strip production line, the surface defect information of the recommendation algorithm is verified and studied. In the case, the weight coefficient of the hybrid weighted recommendation algorithm is determined. The recommendation results of content-based recommendation algorithm, collaborative recommendation algorithm and hybrid weighted recommendation algorithm are calculated respectively. Finally, three main software function modules of the recommendation algorithm for surface defect matching information of cold rolled strip are designed: defect matching information recommendation module, The database module and the text content information database module are graded, and the function of recommending information algorithm for surface defect matching of cold rolled strip is realized by Visual Studio 2013 software development platform.
【學(xué)位授予單位】：武漢科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TG335.56;TP391.3

【相似文獻(xiàn)】

相關(guān)期刊論文 前5條

1 林雪云;;同好推薦算法的實(shí)踐[J];武漢工程大學(xué)學(xué)報;2014年08期

2 石麗麗;劉茜領(lǐng);張國東;;基于集團(tuán)序推薦輸出的協(xié)同過濾推薦算法[J];鄭州輕工業(yè)學(xué)院學(xué)報(自然科學(xué)版);2012年02期

3 劉洋;李海洋;王育才;;一種基于聚類技術(shù)的免疫推薦算法[J];遼寧石油化工大學(xué)學(xué)報;2011年04期

4 徐守坤;莊福寶;;云環(huán)境下基于資源類別聚合的算法[J];常州大學(xué)學(xué)報(自然科學(xué)版);2014年02期

5 ;[J];;年期

相關(guān)會議論文 前10條

1 王韜丞;羅喜軍;杜小勇;;基于層次的推薦:一種新的個性化推薦算法[A];第二十四屆中國數(shù)據(jù)庫學(xué)術(shù)會議論文集（技術(shù)報告篇）[C];2007年

2 唐燦;;基于模糊用戶心理模式的個性化推薦算法[A];2008年計算機(jī)應(yīng)用技術(shù)交流會論文集[C];2008年

3 秦國;杜小勇;;基于用戶層次信息的協(xié)同推薦算法[A];第二十一屆中國數(shù)據(jù)庫學(xué)術(shù)會議論文集（技術(shù)報告篇）[C];2004年

4 周玉妮;鄭會頌;;基于瀏覽路徑選擇的蟻群推薦算法:用于移動商務(wù)個性化推薦系統(tǒng)[A];社會經(jīng)濟(jì)發(fā)展轉(zhuǎn)型與系統(tǒng)工程——中國系統(tǒng)工程學(xué)會第17屆學(xué)術(shù)年會論文集[C];2012年

5 蘇日啟;胡皓;汪秉宏;;基于網(wǎng)絡(luò)的含時推薦算法[A];第五屆全國復(fù)雜網(wǎng)絡(luò)學(xué)術(shù)會議論文（摘要）匯集[C];2009年

6 梁莘q，

本文編號：1495755