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Financial risk evaluation method of blockchain digital currency based on cart algorithm

WEB INTELLIGENCE 2022年第2期20卷 143-151页

作者： Fan, Xiuling Lv, Haiyang Yantai Nanshan Univ Dept Comp Sci Yantai 265713 Peoples R China Yantai Nanshan Univ Engn Coll Yantai 265713 Peoples R China

In order to overcome the problems existing in traditional financial risk evaluation methods, such as high generalization error and fitting degree with actual value, this paper designs a financial risk evaluation method of blockchain digital currency based on cart algorithm. After screening and ranking the financial risk indicators of blockchain digital currency, the financial risk level of blockchain digital currency is determined by combining cart algorithm. Finally, by calculating the covariance matrix of the financial risk decision matrix, the positive ideal solution and the negative ideal solution of the financial risk are found, and then the final evaluation result is obtained by combining the progress of the financial risk. Experimental results show that the minimum generalization error of this method is only 0.021, the fitting degree of the obtained results and the actual risk can reach 98.0%, and the maximum risk accuracy can reach 0.978.

关键词： Blockchain finance digital currency cart algorithm financial risk assessment

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Design of an international trade target supplier evaluation system based on cart algorithm

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第3期18卷 2439-2454页

作者： Liu, Rui Ganzhou Agr Coll Ganzhou Jiangxi Peoples R China

International trade, as an important component of economic exchange between countries, is of great significance for the economic development of each country and international cooperation. In international trade, the selection and evaluation of suppliers has always been a key issue. To ensure the smooth progress of trade and the controllability of quality, it is necessary to establish a target supplier evaluation system. This article used the cart (Classification and Regression Tree) algorithm to help identify and analyze the impact of key factors on supplier evaluation and classify and evaluate suppliers. The international trade target supplier evaluation system based on the cart algorithm was also constructed, and its performance was tested in the experimental section and compared with the international trade target supplier evaluation system based on traditional algorithms. According to the experimental results, it can be concluded that both the traditional algorithm and the cart algorithm performed well in terms of application effectiveness and system user satisfaction. In terms of application effectiveness, the average score of traditional algorithms was 4.3, with a rating range of 3.8 to 4.9, while the average score of the cart algorithm was 4.6, with a rating range of 4.2 to 5.0. The satisfaction rating of system users on the cart algorithm was slightly higher than that of traditional algorithms, indicating that the cart algorithm has better application effectiveness and user satisfaction in the design of international trade target supplier evaluation systems. The design of an international trade target supplier evaluation system based on the cart algorithm can also help enterprises reduce trade risks and improve the stability and reliability of the supply chain. It has important practical significance and application value for further promoting the development of international trade.

关键词： Supplier evaluation system cart algorithm international trade procurement efficiency supply chain

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Construction of New Media Art Model by Using the cart algorithm and AIGC

Construction of New Media Art Model by Using the CART Algori...

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International Conference on Informatics Education and Computer Technology Applications (IECA)

作者： Ye, Caixian Xu, Lijun Tang, Jun Guangzhou Xinhua Univ Informat & Intelligent Engineer Sch Guangzhou Peoples R China Guangzhou Xinhua Univ AI & Data Sci Sch Guangzhou Peoples R China

ISBN: (纸本)9798350375343;9798350375336

This paper mainly focuses on teenagers under the age of 15 to conduct experimental tests to study their physical and psychological responses when using new media art works, just as dopamine, heart rate, eye tracking, brain wave monitoring, etc., to analyze user residence time and preferences. Then through questionnaire survey, in-depth interviews and other ways to obtain users' experience feedback on new media art works, to understand the user's cognitive, emotional, behavioral and other experience of art works. Analyze the interaction process between users and new media art works, explore the interactive relationship between users and products, and understand users' engagement, emotional input and other experiences. New technology just as the cart algorithm and AIGC is then used to process the data to ensure the reliability and validity of the experimental samples. The construction of the experimental model should also consider the requirements of minimum cost, minimum manpower, minimum time, maximum coverage, etc. The construction of the experimental model is a process of gradual improvement. The new media art model is optimized according to the needs of users, ensuring that users of the same group are trained in different time periods, and modifying the model in real time. After comparing the data of the three types of theme model tests, the model with the highest score and the lowest modification rate is the best solution.

关键词： machine learning cart algorithm AIGC new media art

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Analysis of Customer Churn Prediction in Telecom Sector Using cart algorithm 1st

Analysis of Customer Churn Prediction in Telecom Sector Usin...

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1st International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI)

作者： Rai, Sandeep Khandelwal, Nikita Boghey, Rajesh Technocrats Inst Technol Excellence Dept Comp Sci & Engn Bhopal India

ISBN: (纸本)9789811500299;9789811500282

Predicting client churn in telecommunication industries becomes the most significant topic for analysis in recent years. Because its helps in detecting which customer are likely to change or cancel their subscription to a service. Analysis of information that is extracted from telecommunication companies will help to seek out the explanations of client churn and also uses the knowledge to retain the purchasers. Thus, predicting churn is extremely necessary for telecommunication firms to retain their customers. During this paper, we have designed the classification model using call tree, evaluated the performance measures, and compared its performance with logistic regression model.

关键词： Classification Churn prediction Telecom data Logistic regression model Customer retention cart algorithm

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The Application of cart algorithm in Analyzing Relationship of MOOC Learning Behavior and Grades 1

The Application of CART Algorithm in Analyzing Relationship ...

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1st Annual International Conference on Sensor Networks and Signal Processing (SNSP)

作者： Xiao, Bing Liang, Meiping Ma, Junliang Shaanxi Nounal Univ Sch Comp Sci Xian Shaanxi Peoples R China Minist Educ Key Lab Modern Teaching Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781538674130

Nowadays, with the coming of education informatization, MOOC is developing vigorously. Accumulating a large n umber of students' behavior data in the online teaching platforms has been widely concerned. In this paper, using the cart algorithm of decision tree, we analyze the data of MOOC about medical science in Stanford University. And then we explore the factors and importance influencing the test results. The study found that the total number of questions, the score of assignments, and the number of quizzes could be used as an important indicator of performance prediction. We also found that the decision tree model constructed by this course is as accurate as 90%, and the value of cart algorithm for online learning effect is tested. Finally, based on the related research of Stanford University, the paper puts forward some suggestions to improve the service mode of MOOC platforms.

关键词： online learning behavior cart algorithm achievements

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A Study on Push Technology of Intelligent Agriculture Service Information Based on cart algorithm

A Study on Push Technology of Intelligent Agriculture Servic...

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International Conference on Robots and Intelligent System (ICRIS)

作者： Yan, Hui Hu, Haiyan Yu, Ping Changchun Inst Technol Changchun 130012 Peoples R China Jilin Prov Sci & Technol Innovat Ctr Phys Simulat Changchun 130012 Peoples R China Jilin Business & Technol Coll Dept Informat Engn Changchun 130507 Peoples R China

ISBN: (纸本)9781728126326

In this paper, the information push service will be studied to realize the customization of messages according to precise space-time and crop message, and the meteorological message, monitoring data and decision-making model of the designated area in a specific time will be combined to decide whether to apply fertilizer and the amount of fertilizer. The push technology will be combined according to the decision tree based on cart algorithm for sample set to verify and make decision on information and the push server based on XMPP protocol will be built to recommend decision information for users automatically and intelligently. The farm operation database is established to push the farm operation information to different regions on a time scale, which directly guides the actual production of users and ensures the timeliness of information and high efficiency of management.

关键词： cart algorithm Intelligent Agriculture Information push technology

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Well Group Connectivity Relations Discriminate based on cart algorithm

Well Group Connectivity Relations Discriminate based on CART...

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International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Liang, Jisheng Zheng, Wei Yuan, Zibo Northeast Petr Univ Dept Comp & Informat Technol Daqing 163318 Peoples R China

ISBN: (纸本)9783038350125

Up to now, the common method of reservoir well group that is dynamic connectivity, it mainly includes tracer testing, stress testing, well testing, and numerical simulation. The implementation of these methods is more complex, expensive, high cost, and will affect the normal production of the oilfield. Because of the convenient injection and dynamic data it can get convenient. This paper presents a method that using dynamic reservoir development data inverse well group connectivity. cart algorithm analysis and extraction of potential knowledge from the oilfield development. It establish direct mapping of logging data and well group connectivity relationship. Experiments show that using dynamic data to study well group connectivity relationship can greatly reduce the cost and as a result has a higher accuracy.

关键词： component Connectivity cart algorithm Injection and production wells system Oilfield

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C_cart: An instance confidence-based decision tree algorithm for classification

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INTELLIGENT DATA ANALYSIS 2021年第4期25卷 929-948页

作者： Yu, Shuang Li, Xiongfei Wang, Hancheng Zhang, Xiaoli Chen, Shiping Minist Educ Key Lab Symbol Computat & Knowledge Engineer Changchun 130012 Jilin Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun Jilin Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Jiangsu Peoples R China CSIRO Data61 Sydney NSW Australia

In classification, a decision tree is a common model due to its simple structure and easy understanding. Most of decision tree algorithms assume all instances in a dataset have the same degree of confidence, so they use the same generation and pruning strategies for all training instances. In fact, the instances with greater degree of confidence are more useful than the ones with lower degree of confidence in the same dataset. Therefore, the instances should be treated discriminately according to their corresponding confidence degrees when training classifiers. In this paper, we investigate the impact and significance of degree of confidence of instances on the classification performance of decision tree algorithms, taking the classification and regression tree (cart) algorithm as an example. First, the degree of confidence of instances is quantified from a statistical perspective. Then, a developed cart algorithm named C_cart is proposed by introducing the confidence of instances into the generation and pruning processes of cart algorithm. Finally, we conduct experiments to evaluate the performance of C_cart algorithm. The experimental results show that our C_cart algorithm can significantly improve the generalization performance as well as avoiding the over-fitting problem to a certain extend.

关键词： Degree of confidence cart algorithm generalization classification machine learning

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An Improved algorithm for cart based on the Rough Set Theory

An Improved Algorithm for CART based on the Rough Set Theory

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4th Global Congress on Intelligent Systems (GCIS)

作者： Wang, Weiguang Wang, Cong Gao, Wanlin Li, Jinbin Beijing Univ Posts & Telecommun Minist Educ Key Lab Trustworthy Distributed Comp & Serv BUPT Sch Comp Sci Beijing Peoples R China China Agr Univ Coll Informat & Elect Engn Beijing 100094 Peoples R China China PLA Gen Hosp Clin Data Ctr Beijing Peoples R China

ISBN: (纸本)9781479928859

Data prediction and classification is a critical method in medical nutrition data analysis area. As for the characteristics of being intuitive, efficient and easy to understand, the decision tree algorithm is widely used in this field. However, the classification rules extracted from the decision tree are not the most simple and efficient. The paper analyzes the classical decision tree algorithm cart, and proposes a new improved algorithm R2-cart. The core idea of the advanced algorithm is, in order to simplify the classification rules and tree, combining cart algorithm with rough set theory to conduct the attribute and rule reduction on the classification rules of decision tree. The experiment, which compares the Original cart algorithm with the improved algorithm, shows that the improved algorithm has much better classification efficiency with achieving a simple and efficient classification rule set at the same time. This improved algorithm has a potential practical value for large-scale medical nutrition data of classification and predictive analysis.

关键词： cart algorithm rule reduction attribute reduction classification tree rough set theory data mining

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Implementation of cart (Classification and Regression Trees) algorithm for Determining Factors Affecting Employee Performance 4

Implementation of CART (Classification and Regression Trees)...

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4th International Conference on Computing, Engineering, and Design (ICCED)

作者： Pahmi, Samsul Saepudin, Sudin Maesarah, Nira Solehudin, Ujang Isa Wulandari Nusa Putra Univ Dept Informat Syst Sukabumi Indonesia

ISBN: (纸本)9781538693780

The purpose of this research is to identify the problems that affect the performance of employees in the company. This research is a type of quantitative research involving data with different types ranging from nominal, continuous, categorical, ordinal and using 15 independent variables and 1 dependent variable. The population in this research are all employees of some companies in Sukabumi Indonesia. The sample used was 120 employees and the determination of the sample used a random sampling method. Methods of data collection in this study were questionnaires, interviews, and documentation. Data analysis method uses cart (Classification and Regression Trees) algorithm because it involves many kinds of data. The results showed that there are five variables that can be used for work motivation, corporate social environment, job type, leadership style, and organizational support (company policy). From these variables, the best formula can be generated to improve the performance of the employee is: increase the motivation of work (X1), making the company more conducive social environment (x11), divide the types of work (X14), which became more specific to be done individually, and if an employee is required to work in a team, it should be supported by specific policy organization/ company (X3). Of the overall variables, the most influential factor in the performance of employees is the motivation of work, when higher the motivation of work, then the possibility of increased employee performance could be higher.

关键词： Performance employees motivation environment type of work job type cart algorithm

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