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A Novel prediction of sales and purchase forecasting for festival season of Hypermarkets with customer dataset using apriori algorithm instead of FP-Growth algorithm to improve the accuracy 1

A Novel prediction of sales and purchase forecasting for fes...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Karthik, Somu Velu, C.M. Saveetha University Chennai India

ISBN: (纸本)9781607685395

To predict the novel and to Forecast sales for festival season Hypermarkets. A total of 484 samples were collected from market datasets available in kaggle. For this two algorithms were used, one is the FP-Growth algorithm and another is apriori algorithm, both the algorithms were executed and compared for accuracy. aprioriachieved accuracy, precision, sensitivity and specificity of 73 %,75%,78%and 80% respectively compared to 71%,73%,76%,75% and 78% by FP-Growth algorithm, 87.4%, 88.2%, 89.2% and 93% respectively compared to 80.1%, 83.39%, 84% and 86.20% by apriori algorithm. The results were obtained with a level of significance (p © The Electrochemical Society

关键词： apriori algorithm Artificial Intelligence FP-Growth algorithm Itemsets Machine Learning Novel prediction Recursive Feature Elimination Transaction datasets

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RESEARCH ON THE APPLICATION OF apriori algorithm IN THE TEACHING OF BALL SPORTS TECHNIQUES AND TACTICS

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SCALABLE COMPUTING-PRACTICE AND EXPERIENCE 2024年第1期25卷 383-394页

作者： An, Jianqun Zhao, Yongfeng Lingnan Normal Univ Coll Sports Sci Zhanjiang 524048 Peoples R China

To address the problem that technical and tactical aspects of ball games have a large impact on match-winning, association rules are used to mine and analyse the data. Item constraint terms are added to the original apriori algorithm to reduce the generation of redundant data, and the operational efficiency of the improved association rules is improved with the aid of the GSA-PSO algorithm to give full play to the fast convergence advantage of the hybrid algorithm. The experimental results show that the algorithm proposed in the study is more convergent than the apriori algorithm, and the former has fewer iterations on average in the single-peaked function;the overall search accuracy is significantly improved. The algorithm is also less disturbed by the dataset than the apriori algorithm, with an average running time of 19.23s, 21.54s and 25.61s for dataset sizes of 200, 500 and 1000 respectively. The deviation rate between the predicted and actual coaching strategies was less than 5% and the scoring tolerance rate was between 0.04 and 0.10. It indicates that the algorithm proposed in the study can improve the efficiency of data analysis, which is conducive to the development of a perfect ball sport technical and tactical scheme and promote the stability of ball sport technical and tactical development.

关键词： apriori algorithm GSA-PSO Association Rules Sports Teaching Tactics Data Mining

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Toward Enhanced Customer Transaction Insights: An apriori algorithm-based Analysis of Sales Patterns at University Industrial Corporation

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第2期15卷 601-609页

作者： Huaman Llanos, Alex Alfredo Quinones Huatangari, Lenin Yalta Meza, Jeimis Royler Huaman Monteza, Alexander Adrianzen Guerrero, Orestes Daniel Rodriguez Estacio, John Smith Natl Univ Jaen Informat & Language Ctr Jaen Peru Natl Univ Jaen Data Sci Res Inst Jaen Peru Natl Univ Jaen Direct Prod Ctr Goods & Serv Jaen Peru Natl Univ Jaen Social Sci Acad Dept Jaen Peru Natl Univ Jaen Univ Ind Corp Jaen Peru

The University Industrial Corporation (CIU) at the National University of Jaen offers a range of consumable products, encompassing nectar, water, coffee, chocolate, and chocoteja. However, its sales transactions function without a systematic analysis. To address this, the study gathered and analyzed sales data from March to November 2023, aiming to identify and delineate associations among frequently co-purchased products, revealing underlying interdependencies and associations. Employing text mining methodologies, this study preprocessed and analyzed 1542 sales records using the apriori algorithm, culminating in the extraction of 17 association rules. Among these rules, three standout associations were uncovered: the purchase of chocolate, chocoteja and water suggests a purchase of nectar;chocolate, nectar and water acquisitions correlate with chocoteja purchases;lastly chocolate and nectar purchases are associated with chocoteja acquisitions. These findings provide insights to augment potential production adjustments within the CIU, enabling the leveraging of established associations to boost sales and revenue. Moreover, the identified rules serve as a cornerstone for decision- makers, actionable guidance for stakeholders, enabling the identification of co-purchased products, fostering informed production planning, fine-tuning marketing strategies for customer relationship management (CRM), and enhancing CIU's market competitiveness and profitability.

关键词： apriori algorithm association rules Customer Relationship Management (CRM) decision making text mining

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Optimization of Hemorrhagic Stroke Strategy Based on Random Forest and apriori algorithm 24

Optimization of Hemorrhagic Stroke Strategy Based on Random ...

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Proceedings of the 2024 4th International Conference on Computational Modeling, Simulation and Data Analysis

作者： Tao Lin Yu Wan Dejin Ma Yiheng Zhang Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798400711831

After a hemorrhagic stroke, patients may experience increased hematoma expansion and changes in edema volume. Timely and effective prognosis diagnosis and evaluation can improve the quality of life and survival rate of patients. This article is based on a data-driven approach, integrating imaging features and clinical patient information, and using random forest and apriori algorithms for analysis, diagnosis, prediction, and evaluation. This provides strong support for clinical decision-making. The research results indicate that the model can effectively predict the probability of hematoma enlargement in patients and evaluate the influence of key factors such as edema volume.

关键词： apriori algorithm

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An Improved apriori algorithm for Association Mining Between Physical Fitness Indices of College Students

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING 2021年第9期16卷 235-246页

作者： Pan, Tao Guizhou Univ Commerce Guiyang Peoples R China

The physical fitness of college students can be evaluated scientifically based on the data of physical education (PE). This paper firstly relies on the apriori algorithm to mine the hidden correlations between the physical fitness indices from the PE data on college students, and identify the indices closely associated with the physical fitness of college students. Then, the apriori algorithm was improved to reduce the time complexity of association rule mining. Based on the improved algorithm, it was learned that the correlation coefficients of several indices surpassed the minimum support of 0.2 and minimum confidence of 0.7, reflecting their important impacts on physical fitness. Thus, physical fitness of college students is significantly influenced by speed, endurance, flexibility, and vital capacity, but not greatly affected by height and weight. The research results provide an important guide for the test and curriculum designs of PE for college students.

关键词： apriori algorithm data mining association rules physical education (PE) physical fitness indices

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Application of the apriori algorithm in Soccer Games 23

Application of the Apriori Algorithm in Soccer Games

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Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications

作者： Tao Xie Yaxian Hao Yanyuan Xing Kyungil University South Korea School of Mathematics and Computer Science Shanxi Normal University China Department of Mathematics Changzhi University China

ISBN: (纸本)9798400708268

This study focuses on the application of the apriori algorithm in soccer games, specifically examining data from Real Madrid's five matches during the quarter-finals, semi-finals, and final stages of the 2016-2017 UEFA Champions League season. The analysis primarily revolves around the concept of "scoring opportunities" which is explained in the literature. Utilizing the apriori algorithm, the study examines the relationship between scoring opportunities, individual players, and frequent player combinations. Furthermore, the study identifies a significant link between the "frequent player combinations" and the players responsible for creating scoring opportunities, thereby identifying the best player combination. Additionally, the paper analyzes the area association in the team's attacking strategies, examining the main attack patterns employed by Real Madrid. Furthermore, the study explores the correlation between players and their playing time, ensuring that the results of the data analysis align with the actual dynamics of soccer games.

关键词： apriori algorithm Attacking patterns Best combination Data Mining Scoring opportunities

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An Efficient Approach to Association Rule Mining Using the apriori algorithm: A Case Study on Enhancing Sports Performance in University Students 24

An Efficient Approach to Association Rule Mining Using the A...

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Proceedings of the 2024 International Conference on Sports Technology and Performance Analysis

作者： Wanting Lv Shan Li School of Physical Education Xi'an Physical Education University Xi'an China

ISBN: (纸本)9798400712234

The 2022 edition of the Dietary Guidelines for Chinese Locals indicates that the occurrence of overweight and excessive weight among Chinese university students gets on the rise, while their sporting activities efficiency is decreasing. This write-up offers research study focused on finding possible remedies to boost university students' sports performance. An association policy mining method based on the apriori algorithm was made use of to discover the relationship between different workout programs and the failing indicators observed in fitness tests. The results revealed that HIIT performed at 90%-97% of HRmax worked in reducing body fat percentage amongst pupils with an overweight BMI and was specifically beneficial for boosting explosive rate and muscular cardio endurance. On the other hand, HIIT conducted at 80%-89% HRmax was a lot more efficient in improving cardiorespiratory feature and muscular stamina. Furthermore, MICT at 75%-79% HRmax can effectively decrease body fat percentage and enhance adaptability in students with overweight BMI. This paper highlights the strong link between computer technology and the advancement of tailored exercise plans, demonstrating just how computer system formulas can extra precisely enhance the sports performance of university students.

关键词： apriori algorithm

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Research on Natural Disasters Interdependent based on apriori algorithm 23

Research on Natural Disasters Interdependent based on Aprior...

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Proceedings of the 2023 6th International Conference on E-Business, Information Management and Computer Science

作者： Shiying Wang Haikun Teng Rong Sun Heihe University China and Harbin University of Commerce China Heihe University China

ISBN: (纸本)9798400709333

Natural disasters are abnormal phenomena occurring in nature that human beings depend on, which affect people's production and life and threaten human life. They are one of the most severe challenges that human beings have faced in the past, present and future. Therefore, disaster prevention and reduction has always been the main goal of governments and relevant personnel of all countries. At present, there are many theories and models for a certain kind of natural disaster, but few studies on the correlation between different types of natural disasters. In this paper, earthquake and typhoon disasters are taken as examples. Firstly, big data technology is used to extract tens of thousands of disaster data through Python language, and data is preprocessed from three aspects: numerical protocol, dimension reduction and dimension transformation. Secondly, the apriori algorithm is used to create an earthquake - typhoon association analysis model. By generating strong association rules, the frequent item set is calculated and the association rules are output. The effectiveness and readiness of the rules are guaranteed according to support control, confidence control and lift control. Finally, in order to make the results more intuitive, easy to understand and use, the research results are displayed visually, and the final conclusion is drawn.

关键词： apriori algorithm Big data Earthquake Interdependent Natural disaster Typhoon

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Research on the Construction and Decision Optimization of Dynamic Evaluation System for Accounting Education Quality Based on apriori algorithm 25

Research on the Construction and Decision Optimization of Dy...

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Proceedings of the 2025 International Conference on Big Data and Informatization Education

作者： Yang Wang School of Economics and Management Dalian University of Science and Technology Dalian Liaoning China

ISBN: (纸本)9798400714405

The deep integration of artificial intelligence and big data technology puts forward higher requirements for the dynamic adaptability of education management system. Aiming at the problems such as weak curriculum relevance and lagging management decisions in the quality assessment of accounting education, this study constructs a dynamic assessment system for the quality of accounting education based on the apriori algorithm and multi-source data-driven. By integrating 2.1TB of daily structured and unstructured data (including accounting practice operation logs, course grades, and case teaching videos), the system realizes three core functions: course group association rule mining (support level 0.09, confidence level 0.62), learner 32-dimensional ability portrait modeling and resource accurate recommendation (match level 82%). The empirical results show that the system can improve the efficiency of management decision making by 58%, and the satisfaction of students' personalized service is 91%, and the time series analysis validates the significant promoting effect of data structure courses on professional competence cultivation (Pearson coefficient 0.62, p<0.01). The research breaks through the static assessment framework and provides a closed-loop solution of “monitoring - early warning - optimization” for Accounting Education management, but it needs to further explore multi-modal data fusion and regional collaboration mechanisms.

关键词： apriori algorithm

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Machine learning approaches for prediction of properties of natural fiber composites : apriori algorithm

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AUSTRALIAN JOURNAL OF MECHANICAL ENGINEERING 2023年第5期21卷 1790-1805页

作者： Balasundaram, R. Devi, Sathiya S. Balan, Sakthi G. SRM Inst Sci & Technol Mech Engn Tiruchirappalli Campus Tiruchirappalli Tamil Nadu India Anna Univ Univ Coll Engn Dept Informat Technol BIT Campus Trichy Tamil Nadu India Vellore Inst Technol Sch Mech Engn Vellore Campus Vellore Tamil Nadu India

The selection of materials with the required properties was developing rapidly. There is no single rule to choose suitable material for a particular product. The complexes interrelation among the properties of composites makes more difficult to suggest suitable material for material scientist. The forecasting of relationship among material properties with throughput screening methods can help for the discovery of novel materials. The conventional way of selection of material need more investigations and time consuming. Recently, machine learning approaches are widely used in mechanical domain. Hence in this work, machine learning-based method was proposed to discover the relationship between the properties of natural fibres composites. To apply machine learning approach, there are 26 different natural fibres composites of Coir, Jute, Banana etc. were taken in to consideration. These materials are reinforced with pure export with different manufacturing methods such as Hand layup, Spray layup, Hot press moulding, and Compression moulding to produce the samples as per ASTM standards. The properties like density, tensile strength, hardness etc. were measured and interrelation among them was recognised using proposed method.

关键词： Epoxy composite natural fibre composites machine learning apriori algorithm association analysis

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