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Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and apriori algorithm

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Chinese Journal of Mechanical Engineering 2022年第5期35卷 66-86页

作者： Cunbo Zhuang Ziwen Liu Jianhua Liu Hailong Ma Sikuan Zhai Ying Wu Laboratory of Digital Manufacturing School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314000China Shanghai Institute of Spacecraft Equipment Shanghai 200240China

The assembly process of aerospace products such as satellites and rockets has the characteristics of single-or small-batch production,a long development period,high reliability,and frequent *** to predict and avoid quality abnormalities,quickly locate their causes,and improve product assembly quality and efficiency are urgent engineering *** the core technology to realize the integration of virtual and physical space,digital twin(DT)technology can make full use of the low cost,high efficiency,and predictable advantages of digital space to provide a feasible solution to such ***,a quality management method for the assembly process of aerospace products based on DT is *** that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection,the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly *** apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to *** implementation of the proposed approach is described,taking the collected centroid data of an aerospace product’s cabin,one of the key quality data in the assembly process of aerospace products,as an example.A DT-based quality management system for the assembly process of aerospace products is developed,which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

关键词： Quality management Digital twin Assembly process Aerospace product Grey Markov model apriori algorithm

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Misdiagnosis Features of Ancient Clinical Records Based on apriori algorithm

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Chinese Medicine and Culture 2020年第1期3卷 50-53页

作者： Ling Yu Department of Basic Theroy of TCM Faculty of Basic MedicineShanghai University of Traditional Chinese MedicineShanghaiChina

Objective:To analyze misdiagnosis features in clinical cases of“Classified Medical Cases of Famous Physicians”and“Supplement to Classified Case Records of Celebrated Physicians.”Materials and Methods:Two hundred and five ancient misdiagnosed cases were analyzed in aspects of locations(exterior-interior type,qi-blood type and Zang‑Fu organs type)and patterns(heat-cold type and deficiency-excess type)by apriori algorithm ***:The main types of misdiagnosis in those medical casesare as follows::Zang‑Fu location misjudgment,misjudging the interior as the exterior,misjudging deficiency pattern as excess pattern,and misjudging cold pattern as heat *** them,the most outstanding type is the misjudgment of deficiency–cold pattern as excess–heat ***:(1)Accurate judgment of location and differentiation of deficiency and excess patterns are the key points in diagnosing the diseases *** confusion of true deficiency–cold and pseudo‑excess–heat pattern should be taken seriously.(2)Data mining on ancient clinical cases offers a new methodology for assisting clinical diagnosis of traditional Chinese medicine.

关键词： Ancient clinical cases apriori algorithm classified medical cases of famous physicians data mining misdiagnosis features supplement to classified case records of celebrated physicians

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A Forensic Investigation of Terrorism in Nigeria: An apriori algorithm Approach

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Journal of Information Security 2021年第4期12卷 270-280页

作者： Aamo Iorliam Raymond U. Dugeri Beatrice O. Akumba Samera Otor Department of Mathematics & Computer Science BSU Makurdi Nigeria

Investigations towards studying terrorist activities have recently attracted a great amount of research interest. In this paper, we investigate the use of the apriori algorithm on the Global Terrorism Database (GTD) for forensic investigation purposes. Recently, the apriori algorithm, which could be considered a forensic tool, has been used to study terrorist activities and patterns across the world. As such, our motivation is to utilise the Apriori algorithm approach on the GTD to study terrorist activities and the areas/states in Nigeria with high frequencies of terrorist activities. We observe that the most preferred method of terrorist attacks in Nigeria is through armed assault. Again, our experiment shows that attacks in Nigeria are mostly successful. Also, we observe from our investigations that most terrorists in Nigeria are not suicidal. The main application of this work can be used by forensic experts to assist law enforcement agencies in decision making when handling terrorist attacks in Nigeria.

关键词： Forensics Terrorism Nigeria apriori algorithm

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An Improved apriori algorithm on the Frequent Itemse

An Improved Apriori Algorithm on the Frequent Itemse

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2013教育技术与信息系统国际会议

作者： Xiang Fang Department of Department of Computer Science Shandong Institute of Business and Technology

According to the problem that the traditional apriori algorithm needs to scan database frequently, an improved strategy and corresponding algorithm is put forward in this paper. This method, only when L1-candidates are produced, scans the transaction database D. The rest frequent itemsets are produced through the scan of preceding result in place of the transaction database. The improved algorithm reduces I/O load and has higher efficiency.

关键词： Association Rule apriori algorithm Frequent Itemse

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Value reduction in rough sets based on apriori algorithm

Value reduction in rough sets based on Apriori algorithm

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2010 Chinese Control and Decision Conference

作者： Yuliang Ma,Zhizeng Luo School of Automation,Hangzhou Dianzi University,Hangzhou,310018

Aiming at value reduction,a kind of RSVR algorithm was presented based on support in association rules via apriori algorithm.A more effective reduction table can be obtained by deleting those rules with less support according to least support—*** reduction feasibility of this algorithm was achieved by reducing the given decision table. Testing by UCI machine learning database and comparing this algorithm with least value reduction algorithm indicate the validity of RSVR algorithm.

关键词： Association rules Value reduction Support apriori algorithm Rough sets

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The Research of Improved apriori algorithm for Mining Association Rules

The Research of Improved Apriori Algorithm for Mining Associ...

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2008 11th IEEE International Conference on Communication Technology(ICCT2008)

作者： WanjunYu 1 XiaochunWang 1 Fangyi Wang 2 Erkang Wang 1 Bowen Chen 1 1 School of Information and Engineering Northeast Dianli University Jilin Jilin province 132012 China 2 School of General Division Department Jilin Industrial Economics Jilin Jilin province 132012 China

Association rules are the main technique for data *** algorithm is a classical algorithm of association rule mining Lots of algorithms for mining association rules and their mutations are proposed on basis of apriori algorithm,but traditional algorithms are not *** the two bottlenecks of frequent itemsets mining:the large multitude of candidate 2itemsets,the poor efficiency of couting their support,this paper proposes a novel algorithm so called Reduced apriori algorithm with Tag（RAAT）,which reduces one redundant pruning operations of C *** the number of frequent 1-itemsets is n,then the number of connectded candidate 2-itemsets is C n 2,while pruning operations C n *** noval algorithm decreases pruning operations of candidate 2-itemsets,thereby saving time and increasing *** the bottleneck:poor efficiency of couting support,RAAT optimizes subset operation,through the transaction tag to speed up support *** experimental results obtained from tests show that RAAT outperforms original one efficiency.

关键词： data mining association rules apriori algorithm

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Application Of apriori algorithm In Open Experiment

Application Of Apriori Algorithm In Open Experiment

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2011 4th IEEE International Conference on Computer Science and Information Technology(ICCSIT 2011)

作者： Li Mengshan Liu Bingxiang Wu Yan Sub-Institute of Science&Technology and Art JingDezhen Ceramic Institute Jing Dezhen Ceramic Institute Information Engineering Institute

ISBN: (纸本)9781612848334

In this paper, we introduce the basic ideas of Association Rules and apriori algorithm, and analyse the relationship between the booking database of the open experiment and the implementation of apriori algorithm. After the pre-processing of the dataset we have accumulated, we apply the apriori algorithm of Association Rules to mine some related information in the booking database. So we can get some important association information both in the same type experiments and in some independent experiments. Then, we analyse the mined information, get the reasons of the association information, and give some advice to the administration of experiment teaching so as to improve the work efficiency.

关键词： apriori algorithm Association Rules Teaching Reform Open Experiment

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Simulation System of Car Crash Test in C-NCAP Analysis Based on an Improved apriori algorithm

Simulation System of Car Crash Test in C-NCAP Analysis Based...

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2012 International Conference on Solid State Devices and Materials Science(SSDMS 2012)

作者： LI Xiang School of Computer Engineering Huaiyin Institute of Technology

In order to analysis car crash test in C-NCAP, an improved algorithm is given based on apriori algorithm in this paper. The new algorithm is implemented with vertical data layout, breadth first searching, and intersecting. It takes advantage of the efficiency of vertical data layout and intersecting, and prunes candidate frequent item sets like apriori. Finally, the new algorithm is applied in simulation of car crash test analysis system. The result shows that the relations will affect the C-NCAP test results, and it can provide a reference for the automotive design.

关键词： apriori algorithm car crash association rule

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Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining algorithm apriori

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Journal of Contemporary Educational Research 2024年第2期8卷 213-223页

作者： Xuemei Li Edward CJimenez Angeles University Foundation PhD Educ-EMMacArthur HwyAngeles2009 PampangaPhilippines Shandong College of Traditional Chinese Medicine Educational Technology CenterYantai 264199Shandong ProvinceChina

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching *** the help of IBM SPSS Modeler data mining software,this paper uses apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core ***,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

关键词： Grade analysis apriori algorithm Course relevance Data mining

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Novel apriori-Based Multi-Label Learning algorithm by Exploiting Coupled Label Relationship

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Journal of Beijing Institute of Technology 2017年第2期26卷 206-214页

作者： Zhenwu Wang Longbing Cao Department of Computer Science and Technology China University of Mining and Technology(Beijing) The Advanced Analytics Institute University of TechnologySydney

It is a key challenge to exploit the label coupling relationship in multi-label classification（MLC）*** previous work focused on label pairwise relations,in which generally only global statistical information is used to analyze the coupled label *** this work,firstly Bayesian and hypothesis testing methods are applied to predict the label set size of testing samples within their k nearest neighbor samples,which combines global and local statistical information,and then apriori algorithm is used to mine the label coupling relationship among multiple labels rather than pairwise labels,which can exploit the label coupling relations more accurately and *** experimental results on text,biology and audio datasets shown that,compared with the state-of-the-art algorithm,the proposed algorithm can obtain better performance on 5 common criteria.

关键词： multi-label classification hypothesis testing k nearest neighbor apriori algorithm label coupling

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