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Mining Association Rules on Enrollment Information of Higher Vocational Colleges Using the apriori algorithm

JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2019年第4期23卷 775-781页

作者： Li, Tao Qingdao Vocat & Tech Coll Hotel Management Qingdao 266100 Shandong Peoples R China

The enrollment work of higher vocational colleges is an important part of a school's strategic decision-making. Developing a reasonable enrollment plan is highly important for a school's development. Previous enrollment information contains extensive valuable information, which should be used by adopting effective methods of data processing. This study used an improved apriori algorithm to mine the association rules of enrollment information to obtain the factors that affect enrollment. A higher vocational college in Qingdao was taken as the object of study. Three attributes were selected for association rule mining: college entrance exam results, applied majors, and student background. It was found that student registration rates were significantly different under different rules. The data mining results can provide policy support for future enrollment plans.

关键词： association rules data mining apriori algorithm admission information

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Reliability Modeling and Analysis of Ship Communication Network Based on apriori algorithm

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JOURNAL OF COASTAL RESEARCH 2019年第Sup93期000卷 711-716页

作者： Xie, Chao Shi, Peibei Cao, Fengyun Qian, Yanyu Hefei Normal Univ Sch Comp Sci & Technol Hefei 230601 Anhui Peoples R China

Ship communication network is prone to distortion due to crosstalk between ships. In order to improve the accuracy of data transmission and improve communication quality, a reliability modeling method of ship communication network based on apriori algorithm is proposed. The transmission link model of ship communication network is constructed, and the fuzzy PID neural network control model is used to control the reliability of the link forwarding node of ship communication network, so as to realize the optimal deployment of the link forwarding node of ship communication network. Taking output forwarding delay, bit error rate and network throughput as constraint parameters, the reliability modeling objective function of ship communication network is constructed. The optimal parameters are optimized by apriori learning algorithm, and the routing detection protocol of ship communication network is designed. Implementation of network routing optimization design. The simulation results show that the reliability of ship communication network is modeled by this method, the accurate probability of data transmission is improved, the bit error rate of communication network is low, and the quality of ship communication network is improved obviously.

关键词： apriori algorithm ship communication network reliability modeling

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Using The apriori algorithm To Classify The Care Needs Of Patients With Different Types Of Dementia

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PATIENT PREFERENCE AND ADHERENCE 2019年 13卷 1899-1912页

作者： Jhang, Kai-Ming Chang, Ming-Che Lo, Tzu-Ying Lin, Che-Wei Wang, Wen-Fu Wu, Hsin-Hung Changhua Christian Hosp Dept Neurol Changhua Taiwan Changhua Christian Hosp Dept Nucl Med Changhua Taiwan Natl Changhua Univ Educ Dept Business Adm Changhua Taiwan Changhua Christian Hosp Med Div Performance Ctr Changhua Taiwan Ming Dao Univ Dept Holist Wellness Changhua Taiwan Asia Univ Dept M Commerce & Multimedia Applicat Taichung Taiwan

Purpose: To elucidate specific combinations of care needs for people living with dementia (PLWD) and their caregivers according to specific subtypes of dementia. Patients and methods: A cross-sectional study at memory clinics in Changhua Christian Hospital, Taiwan, was conducted. Five hundred and eight people living with dementia and their caregivers joined the dementia collaborative care model. The care team established 15 care needs containing most of quality measures for PLWD and their caregivers. Individualized care plans including different combinations of care needs were addressed through face-to-face assessments. apriori algorithm was used to find specific combinations of care needs for particular groups of PLWD and their caregivers. Results: This study identified the basic care needs of PLWD and caregivers including appropriate scheduling of activities, regular outpatient follow-up treatment, introduction and referral of social resources, referral to family support groups and care skills training, and health education for dementia and behavioral and psychological symptoms of dementia. Patients with Alzheimer's dementia required more care to prevent traffic accidents and getting lost, while patients with vascular dementia required more care to prevent falls. The older (>= 75 years old) PLWD were associated with more needs of fall prevention and care for the mood of the caregiver, especially in the female patients with mild Alzheimer's dementia (CDR = 1). Conclusion: Bundling the needed care needs might be a more effective means to care for a wide variety of patients with dementia.

关键词： people living with dementia behavioral and psychological symptoms of dementia dementia collaborative care model care need apriori algorithm

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Using the apriori algorithm and Copula Function for the Bivariate Analysis of Flash Flood Risk

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WATER 2020年第8期12卷 2223页

作者： Zhong, Ming Wang, Jiao Jiang, Tao Huang, Zhijun Chen, Xiaohong Hong, Yang Sun Yat Sen Univ Sch Geog & Planning Guangzhou 510275 Peoples R China Univ Bristol Water & Environm Management Res Ctr Dept Civil Engn Bristol BS8 1TR Avon England Sun Yat Sen Univ Sch Atmospher Sci Guangzhou 510275 Peoples R China Sun Yat Sen Univ Sch Civil Engn Guangzhou 510275 Peoples R China Univ Oklahoma Sch Civil Engn & Environm Sci Norman OK 73072 USA

Flash flooding is a phenomenon characterized by multiple variables. Few studies have focused on the extracted variables involved in flash flood risk and the joint probability distribution of the extracted variables. In this paper, a novel methodology that integrates the apriori algorithm and copula function is presented and used for a flood risk analysis of Arizona in the United States. Due to the various rainfall indices affecting the flash flood risk, when performing the apriori algorithm, the accumulated 3-h rainfall and accumulated 6-h rainfall were extracted as the most fitting rainfall indices. After comparing the performance of copulas, the Frank copula was found to exhibit the best fit for the flash flood hazard;thus, it was used for a bivariate joint probability analysis. The bivariate joint distribution functions of P-Q, PA-Q, PB-Q, and D-Q were established, and the results showed an increasing trend of flash flood risk with increases in the rainfall indices and peak flow;however, the risk displayed the least significant relation with the duration of the flash flood. These results are expected to be useful for risk analysis and decision making regarding flash floods.

关键词： flash floods copulas apriori algorithm bivariate probability rainfall indices

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APPLICATION OF apriori algorithm IN THE LAMINATION PROCESS IN YACHT PRODUCTION

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POLISH MARITIME RESEARCH 2020年第3期27卷 59-70页

作者： Niksa Rynkiewicz, Tacjana Landowski, Michal Szalewski, Pawel Gdansk Univ Technol 11-12 Gabriela Narutowicza St PL-80233 Gdansk Poland

The article specifies the dependence of defects occurring in the lamination process in the production of yachts. Despite great knowledge about their genesis, they cannot be completely eliminated. Authentic data obtained through cooperation with one of the Polish yacht shipyards during the years 2013-2017 were used for the analysis. To perform a simulation, the sample size was observed in 1450 samples, consisting of 6 models of yachts with closed and open deck. Finding the dependence of the occurrence of specific defects will allow for faster procedures and more effective quality control, which will contribute to lower costs. The use of new methods based on artificial intelligence related to Big Data allows for easier observation of dependencies in the complex structure of data from yacht production. The association rules were defined using the algorithm apriori and define interdependent defects. A number of dependencies were found for the occurrence of production defects not obvious to technologists, but occurring with a high probability of coexistence. The presented research results may allow the planning process of production tasks to be improved.

关键词： apriori algorithm quality control laminate defects

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Research on Improved apriori algorithm Based on Data Mining in Electronic Cases

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INTERNATIONAL JOURNAL OF HEALTHCARE INFORMATION SYSTEMS AND INFORMATICS 2019年第3期14卷 16-28页

作者： Wang, Xiaoli Su, Kui Su, Lirong Mudanjiang Med Univ Mudanjiang Peoples R China

This article makes progress of a commonly used apriori algorithm, and proposes a new apriori algorithm based on event ID. In this article, association rules are gained from massive medical data through the new apriori algorithm. This article proposes and then uses the association rules in the prediction system. This article aims at making the lifestyle-related diseases prediction system provide better service for people, for families and for the whole society. The prediction system can automatically give out health-related information of the user after the person's basic information is put in, and it would also give out some pieces of valuable advice according to the resultant data, helping people realize self-determinant health engagement.

关键词： apriori algorithm Health Lifestyle-Related Diseases Prediction

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Real-Time Decision Making for Underwater Big Data Applications Using the apriori algorithm

Real-Time Decision Making for Underwater Big Data Applicatio...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Albarakati, Hussain Ammar, Reda Elfouly, Raafat Rajasekaran, Sanguthevar Univ Connecticut Comp Sci & Engn Dept Storrs CT 06269 USA Rhode Isl Coll Comp Sci Dept Providence RI 02908 USA

ISBN: (纸本)9781728129990

Underwater acoustic sensor networks (UWASNs) have been introduced as a new technology to extract the data for underwater real-time applications such as seismic monitoring, undersea monitoring and control, oil well inspection, military applications, and disaster prevention. This new technology adds more networking capabilities and enables real-time reporting. However, it is restricted to data sensing, forwarding and data transmission. Specifically, transmitting large volumes of data takes a long time and requires a lot of power to be executed. This has inspired our research activities to focus on building an underwater real-time computing system with the minimum execution time and low power consumption. In our research, valuable information is extracted underwater using data mining or compression algorithms. In our previous study, we proposed a set of real-time underwater embedded system (RTUWES) architectures that can handle multiple network configurations. In this study, we extend our research results to develop information extraction algorithms for big data underwater applications to meet real-time constraints. The system performance is assessed in terms of the end-to-end delay and power consumption. We have built a simulator for practical study. The simulation results are presented to demonstrate the performance of our proposed system based on an information extraction algorithm.

关键词： Underwater acoustic sensor networks underwater embedded system architecture real-time constraints big data apriori algorithm information extraction multipath

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Study on Budget Preparation and Forecast Model Based on apriori Rule algorithm 22

Study on Budget Preparation and Forecast Model Based on Apri...

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Proceedings of the 2022 6th International Conference on Software and e-Business

作者： Minquan Ye Chenhong Zheng Mengzhe Liu Huiying Wu State Grid Fujian Economic Research Institute China

ISBN: (纸本)9798400700095

Association rule algorithm and data mining technology can discover the hidden rules of many target data information, apply relevant technologies to budget management, mine and process the historical budget information and financial revenue and expenditure information of previous years, and can discover some hidden relevant information to guide the budget management of enterprises. This paper introduces the basic concept and algorithm flow of association rules, analyzes the apriori algorithm in detail, and optimizes the association rule mining algorithm after introducing concept level and dimension level. Based on the idea of apriori algorithm to optimize the enterprise budget management process, and build budget analysis and forecast model, which can conduct regression analysis based on historical financial data and forecast the revenue budget of the next year, which is used to guide enterprise budgeting. The model analysis results show that the budget forecasting model in this paper has higher accuracy and reliability than the traditional forecasting methods.

关键词： association rule budget forecast Budgement preparation apriori algorithm

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Reliable frequent itemsets mining with actor-based apriori algorithm

Reliable frequent itemsets mining with actor-based Apriori a...

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44th WILGA Symposium on Photonics Applications and Web Engineering

作者： Puscian, Marek Warsaw Univ Technol Inst Comp Sci Nowowiejska 15-19 PL-00665 Warsaw Poland

ISBN: (纸本)9781510630666

This paper presents an actor-based apriori algorithm enhanced with fault tolerance mechanism. All phases of the algorithm including candidate generation and support counting operations are performed by asynchronous actors. When an error occurs during the execution of the algorithm, calculations are interrupted locally for specific actors. The actor state is restored from the snapshot and the operations that caused the failure are either repeated or skipped. Other actors progress with their current tasks. The algorithm can be executed in parallel and distributed environments. Proposed enhancements have been successfully implemented using JAVA and Akka library. This paper discusses the results of the performance of actor-based apriori algorithm against different datasets. The presented approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

关键词： apriori algorithm frequent items mining fault tolerance algorithm parallelization

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A Combination of Prefixed-Itemset and Database Optimization to Improve apriori algorithm on Hadoop Cluster 4

A Combination of Prefixed-Itemset and Database Optimization ...

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4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Rui, Sun Wuhan Univ Technol Coll Comp Sci & Technol Wuhan Hubei Peoples R China

ISBN: (纸本)9781728146898

A priori algorithm is a classical algorithm in the field of data mining. It is widely used in the research of mining the association rules, but it also has some disadvantages. In this paper, for the three main steps in the execution of the apriori algorithm, we propose a novel method that combines the storage structure of the prefixed-itemset with the database optimization to improve the apriori algorithm on the Hadoop cluster. First, we used the storage structure of the prefixed- itemset to improve the implementation methods of the connection step and the pruning step in the traditional apriori algorithm to increase the execution efficiency of the algorithm. Second, we changed the storage schema of the database. And we converted the original transaction database into the transaction- state matrix to transform the storage pattern of transaction data and enhance the efficiency of the traditional apriori algorithm in the counting step. Then, we combined the properties of the frequent itemsets to improve the iterative termination condition of the algorithm, thus reduced the running time of the algorithm. Finally, we performed MapReduce parallelization improvement on the apriori algorithm optimized by the above steps based on the Hadoop distributed architecture. The experimental results show that compared with the traditional apriori algorithm, the improved apriori algorithm on the Hadoop cluster has improved the execution efficiency greatly.

关键词： Data mining apriori algorithm Prefixed-itemset Transaction-state matrix Hadoop MapReduce

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