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检索条件"主题词=Apriori algorithm"

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Using apriori algorithm on Students' Performance Data for Association Rules Mining

Using Apriori Algorithm on Students' Performance Data for As...

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2nd International Seminar on Education Research and Social Science(ISERSS 2019)

作者： Xiaodong Wu Yuzhu Zeng Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information Processing Fujian Province University

With the development of information technology, many colleges and universities have established student information management system. The long-term operation of the student information management system will generate big data for colleges and universities. Moreover, there exists valuable information in the huge amount of data. Hence, it is necessary to use the data mining method to mine the massive data and get some valuable reference information so as to improve the teaching and management of students. In this paper, the apriori algorithm is used to mine association rules of 34 courses of 100 students majoring in computer science and technology, so as to find out the correlation between courses and the factors that lead to the high or low grades of courses. R is used to conduct the experiment to discover the association rules, and the association rules are analyzed and discussed. The results of data mining on students' achievements in this work are expected to provide a reference for improving the teaching quality of computer science and technology courses.

关键词： data mining apriori algorithm association rules students' achievement analysis

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Research on the Evolution of Power Supply Mode of Park Based on apriori algorithm 2

Research on the Evolution of Power Supply Mode of Park Based...

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2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Tian, Xing Qi, Caijuan Dang, Dongsheng Zhang, Kun Ma, Hongyu Li, Yunping State Grid Ningxia Elect Power Co Ecotech Res Inst Ningxia Peoples R China North China Elect Power Univ Elect Market Res Inst Sch Elect & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781538685495

With the acceleration of the opening process of the distribution side, the power supply modes of various types of industrial parks have undergone great changes. Therefore, it is significant that we study the evolution mechanism of the power supply mode which plays an important role in forecasting the electricity distribution patterns of park and formulating strategies of the relevant principals' market participation. This paper firstly proposes a method of the research on the evolution of power supply mode of park that based on apriori algorithm. Then through mining the association rules of the typical features of the regional power supply and the participating ways of the main users, we have analyzed the evolution mechanism of the power supply mode. At last, the effectiveness of the method is verified by the actual data of a certain province in Northwest China.

关键词： apriori algorithm association rules power supply mode of park data mining

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Study on Association Factors Causing Lung Cancer Based on apriori algorithm

Study on Association Factors Causing Lung Cancer Based on Ap...

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IEEE International Conference on Power, Intelligent Computing and Systems

作者： Mao Xingliang Li Fangfang College of Information System and Management National University of Defense Technology School of Information Science and Engineering Central South University

ISBN: (纸本)9781728137216

In recent years, morbidity of lung cancer has been constantly rising worldwide, particularly in China. The paper, taking relevant data of 2000 patients of lung cancer as research subjects, preprocesses original data, then, studies frequent item set and association rules of apriori algorithm, on which relevant factors causing lung cancer is analyzed. According to experiment results, the association factors proposed by the algorithm in this paper has feasibility and effectiveness in some degree.

关键词： Lung cancer Frequent itemset Association rules apriori algorithm Lung Cancer Association rules Research Subject algorithms RAW DATA Association (Psychology)

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Application of apriori algorithm in Meteorological Disaster Information Mining 15th

Application of Apriori Algorithm in Meteorological Disaster ...

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15th International Conference on Cooperative Design, Visualization, and Engineering (CDVE)

作者： Wang, Chunhui Zhao, Boting Fujian Meteorol Serv Ctr Fuzhou Fujian Peoples R China

ISBN: (纸本)9783030005603;9783030005597

With the progresses of meteorological informatization, large amounts of meteorological data were accumulated. For the better application of these data, this research introduced data mining and applied it to analysis meteorological disaster, which can extract implicit, and potential useful information from a large amount of data in order to guide agricultural production. Meteorological disaster data affecting tea production were analyzed based on apriori algorithm in this research, and the strong association rules between meteorological factors and reduction rate of tea yield were found. The results showed that the reduction rate of tea yield is closely related to the daily minimum temperature in the germination stage. When the daily minimum temperature was less than 5 degrees C, the tea would be affected by the cold and freezing damage and the tea yield would decrease, the lower the temperature, the greater the cold and freezing damage.

关键词： Data mining apriori algorithm Meteorological disaster Cold and freezing damage Tea yield

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Mining on Relationships in Big Data era using Improve apriori algorithm with MapReduce Approach

Mining on Relationships in Big Data era using Improve Aprior...

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International Conference on Advanced Computation and Telecommunication (ICACAT)

作者： Pandey, Kamlesh Kumar Shukla, Diwakar Dr Hari Singh Gour Vishwavidyalaya Dept Comp Sci & Applicat Sagar India

ISBN: (纸本)9781538654729

The current time technology is growing very faster and data is generating very fast so data characteristics have changed in form of data to big data. If anybody wants to mine some related data in big data environment then present data mining algorithm fails to mine relationship in big data and it takes a lot of time for processing. MapReduce approach is a most efficient algorithm in big data framework which handles a huge amount of data and gives fast result. The apriori algorithm is more powerful algorithm for mining on interesting relationships between dataset in any type of databases or same databases. In present time a lot of MapReduce base apriori algorithms are available but its Map and Reduce function run to multiple times and works only for the transaction database. This paper describes what is big data with its characteristics, concept of Association rules with the apriori algorithm in big data, problems in the existing MapReduce base apriori algorithm. We propose new improve MapReduce approach base apriori algorithm for mining on a relationship with the help of given one suitable example where Reduce function runs only one time after running on Map function and this proposed algorithm run on any type of database.

关键词： Big data apriori algorithm MapReduce Approach Association rule mining Big data mining

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Association Rule Analysis of Petrochemical Fire Accidents Based on the apriori algorithm

Association Rule Analysis of Petrochemical Fire Accidents Ba...

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Fire Science and Fire Protection Engineering (ICFSFPE), Conference on

作者： Zhennan Chen Bo Ye China People's Police University Langfang Hebei China

ISBN: (数字)9781728153223

ISBN: (纸本)9781728153230

To analyze the characteristics of petrochemical fire accidents and emergency disposal rules, firstly we did a survey of 947 petrochemical accidents which happened in China from 2013 to 2018. Then, for analyzing the association rules systematically and comprehensively between fire accidents and the causes, a data mining method, apriori algorithm, was applied to mine the potentially rules. The results indicated that: (1) There were 22 causes summarized from all investigation reports, but by quantitatively calculation, only 7 of them were key disaster-causing factors. (2) Five disaster-causing factors can be classified as corporate governance problems, so “Business management has loopholes” was one main risk factors of fire accidents. (3) Some key disaster-causing factors were related with each other. “Failure to implement the main responsibility of production safety”, “Security management has bugs” and “Inadequacy of safe education and training” were related to “Inadequacy of government supervision”.

关键词： petrochemical fires disaster-causing factors association rules apriori algorithm Association rules Accidents Petrochemicals Fire INVESTIGATION REPORT LOOPHOLE

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Applying apriori algorithm and Decision Tree to Promote Data Traffic of Mobile Customers

Applying Apriori Algorithm and Decision Tree to Promote Data...

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IEEE International Conference on Civil Aviation Safety and Information Technology (ICCASIT)

作者： Linlin Luan Huaying Shu School of Economics and Management Beijing University of Posts and Telecommunications No.10 Xitucheng Road Haidian District Beijing China

ISBN: (纸本)9781728125992

Since the penetration rate of mobile phone rises quickly and China mobile telecomm market is almost becoming saturated increasingly, China mobile telecom operators are facing with a slow new subscribers' growth and a decline trend in the average revenue per user (ARPU). China mobile operators are developing strategies to supplement the tapering revenues by promoting mobile value-add service (VAS) and wireless data service in 4G network system. In this paper apriori algorithm and decision tree data mining technique are applied to recommend the market strategy to promote mobile customers' data traffic in data plan and overlap data plan. To ensure the accuracy of the research, we adopt apriori algorithm and decision tree to analyze data of over One hundred and twenty thousand members, over ten provinces. The results show to be very valuable for making strategy recommendations to promote the customers' data traffic in data plan and overlap data plan.

关键词： Data mining Data traffic apriori algorithm Decision tree Mobile telecom market Decision Trees Traffic data data mining penetration rate Mobile Purchasing customers

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Evaluation of Flotation Working Condition Recognition Based on An Improved apriori algorithm

Evaluation of Flotation Working Condition Recognition Based ...

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5th IFAC Workshop on Mining, Mineral and Metal Processing (MMM)

作者： Wang, Xiaoli Song, Chen Xiong, Wei Lv, Xingxiao Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China Changsha Res Inst Min & Met Co Ltd Changsha 410012 Hunan Peoples R China

Based on machine vision and image processing technology, a large number of methods have been proposed for flotation working condition recognition in froth flotation industry. However, in these condition recognition methods, there lacks internal or external evaluation criteria, so that the reliability of the recognition results obtained by the current recognition models is not high for operators. In order to solve this problem, by taking time series of working condition data as the research object, an improved apriori algorithm based on time series is proposed for the evaluation of flotation working condition recognition. Based on the idea of transaction database, the time series data set of working condition is divided into working condition transaction database by an auto-regressive model. Then the improved apriori algorithm is used to find the association rules that contain relations between the time-series of the working condition transaction database to form a rule base for the working condition, which provides the reliability evaluation of the online working condition recognition results based on the association rules. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Froth Flotation Working Condition Evaluation apriori algorithm Association Rule

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A New Method of Resource-Scheduling-Strategy Generation for the Assembly of Complex Products Based on the apriori algorithm 5

A New Method of Resource-Scheduling-Strategy Generation for ...

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5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Wu, Ying Yao, Liya Liu, Jianhua Zhuang, Cunbo Beijing Inst Technol Beijing 100081 Peoples R China

ISBN: (纸本)9781538660058

Complex products, which usually have the characteristics of single or small-batch production and involving many parts, exist a lot of resource-scheduling problems. Since its resource scheduling is often carried out by workers according to their experience, it has poor credibility and applicability without any reference standards. This paper analyzes the assembly process of complex products, classifies the assembly resources, and establishes the resource scheduling model of complex products based on the apriori association rule algorithm Additionally, the model is tested by the historical data of workshop resource allocation. The resource-scheduling-strategy of assembly process is obtained in this paper. It provides references for the future works of intelligently generating the resource-scheduling-strategy of complex-product assembly process.

关键词： Resource-scheduling-strategy apriori algorithm Complex products Assembly process Association rules mining

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Performance Analysis Using apriori algorithm Along with Spark and Python 18

Performance Analysis Using Apriori Algorithm Along with Spar...

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International Conference on Computing and Big Data (ICCBD)

作者： Gao, Fei Bhowmick, Chandrima Liu, Jiangjiang Lamar Univ Dept Comp Sci Beaumont TX 77710 USA

ISBN: (纸本)9781450365406

We have proposed an improved apriori algorithm based on comparing different data structures to obtain a better and improved performance level than presently available approaches. Our approach is to apply on large transaction data where space and time management has been a center of attraction. The improved algorithm is using an existing apriori approach and gives us a more time efficient output. Our approach is implemented on a spark framework along with the PySpark facility that can process data on a much-improved rate compared to the Hadoop framework. Moreover, we have proposed that using python as our programming language has a faster computational rate. We have used a local file system for our data to be stored. In addition, we have shown our time efficiency on spark framework and generated a report using those data to compare spark based analysis on our proposed algorithm. Furthermore, this proposed method can also be effectively applied for a big data mining optimization purpose.

关键词： apriori algorithm item set association rule

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