本文選題：智慧教育　切入點：多約束分配　出處：《南昌大學》2016年碩士論文　論文類型：學位論文

【摘要】：中華五千年歷史中,教育一直都是國家和人民關注的熱點,隨著時間的推移,社會的變遷,教育形式也在一步一步地改變。短短幾十年時間,信息化技術發(fā)展突飛猛進,數(shù)字化教育還沒來得及普遍推廣,基于大數(shù)據(jù)、物聯(lián)網(wǎng)、云計算、人工智能的智慧教育云平臺已經(jīng)開始嶄露頭角了。為了讓教育工作者把更多的時間與精力花在教學理念和教學方法的提升上,我們有必要將一些諸如新生分班、教師排課、考試安排、試卷切題統(tǒng)分、成績分析、學習能力評估等復雜繁瑣卻需要人工操作的工作,通過計算機輔助,使其智能化完成。經(jīng)過調(diào)查分析,發(fā)現(xiàn)新生分班、教師排課、考試安排這類多約束分配、NP難問題是當前學校迫切想解決的棘手問題。針對這三個問題,本文詳細分析了中小學與高校各自不同的要求,總結出必須滿足的硬約束條件和可優(yōu)化的軟約束條件。為了找到解決這三個問題的最佳算法,本文對多約束分配問題的常用算法進行了分析比較,闡述了其基本原理和適用范圍。由于分班問題中新生分數(shù)的規(guī)律性、性別的特殊性、生源地區(qū)域性等特征,本文提出了基于回溯的新生分班算法;而排課與考試都是將課程、教師、教室、班級與時間關聯(lián)起來,并且兩者約束條件具有一定相似性,因此將二者歸納成時間表問題�；跁r間表問題的復雜性,結合遺傳算法的全局解搜索能力和蟻群算法的并行反饋機制,最后確定了基于蟻群遺傳的時間表算法。文中提出的新生分班算法及時間表算法,已實際應用到“智慧教育云平臺”中,實際應用結果表明該算法具有較好的魯棒性,有效地解決了“智慧教育云平臺”中的若干難點問題。
[Abstract]:In the five thousand years of China's history, education has always been the focus of attention of the state and the people. With the passage of time, social changes and educational forms have changed step by step. In a short period of several decades, information technology has developed by leaps and bounds. Digital education has not yet been widely promoted, based on big data, the Internet of things, cloud computing, The intelligent education cloud platform of artificial intelligence has begun to emerge. In order for educators to spend more time and energy on the promotion of teaching ideas and methods, it is necessary for us to divide new students into classes and teachers to schedule classes. The complicated and complicated work, such as examination arrangement, test paper grading, score analysis, learning ability evaluation, which needs manual operation, is accomplished intelligently through computer aid. Through investigation and analysis, it is found that new students are divided into classes and teachers arrange classes. The NP-hard problem of multi-constraint assignment is the thorny problem that schools are eager to solve at present. In view of these three problems, this paper analyzes in detail the different requirements of primary and secondary schools and colleges and universities. In order to find the best algorithm to solve these three problems, the common algorithms of multi-constraint assignment problem are analyzed and compared. This paper expounds its basic principle and application scope. Because of the regularity of freshmen's scores, the particularity of gender and the region of students' origin, this paper puts forward a new class dividing algorithm based on backtracking, and the course scheduling and examination are both general courses. Teachers, classrooms, classes and time are associated with each other, and their constraints are similar, so they are reduced to timetable problems. Combined with the global search ability of genetic algorithm and the parallel feedback mechanism of ant colony algorithm, the algorithm based on ant colony genetic algorithm is finally determined. It has been applied to the "Intelligent Education Cloud platform". The practical application results show that the algorithm is robust and effectively solves some difficult problems in the "Intelligent Education Cloud platform".
【學位授予單位】：南昌大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP18;TP393.09

【參考文獻】

相關期刊論文 前10條

1 白似雪;段仕林;梅舒;;基于關系數(shù)據(jù)庫的關聯(lián)規(guī)則挖掘算法DB-growth[J];南昌大學學報(理科版);2015年01期

2 楊現(xiàn)民;余勝泉;;智慧教育體系架構與關鍵支撐技術[J];中國電化教育;2015年01期

3 張愛華;郭喜躍;陳前軍;;動態(tài)規(guī)劃算法分析與研究[J];軟件導刊;2014年12期

4 王燕;;智慧校園建設總體架構模型及典型應用分析[J];中國電化教育;2014年09期

5 楊現(xiàn)民;余勝泉;;論我國數(shù)字化教育的轉(zhuǎn)型升級[J];教育研究;2014年05期

6 孫瑋;;高校新生分班分寢室一體化系統(tǒng)的設計與實現(xiàn)[J];軟件工程師;2014年05期

7 楊現(xiàn)民;;信息時代智慧教育的內(nèi)涵與特征[J];中國電化教育;2014年01期

8 齊萬華;趙政文;;基于蟻群算法思想的智能考試系統(tǒng)模型研究[J];計算機應用研究;2013年03期

9 顧明遠;;試論教育現(xiàn)代化的基本特征[J];教育研究;2012年09期

10 黃g，

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