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IEEE International Conference on Systems, Man and Cybernetics (SMC)

作者： Wang Wenping Huang Xinhuan Wang Wenzheng Southeast Univ Sch Econ & Management Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781457706530

There have been foreign investors' withdrawal or transference, to a great extent, in lots of domestic regions since the financial crisis. Is the withdrawal of foreign capital subject to the financial crisis or a given stage of the Chinese economy development? Does the financial crisis play the same impacts on the different types of foreign capitals withdrawal? These issues are discussed in this paper. We define the divestment as expansionary divestment and adaptable divestment, and divide the foreign capitals into the manufacturing type, R&D type and operating type. We emphatically discuss how to use the data mining to analyze these problems. The principle and process are described in detail. Especially, a grey correlation degree based decision tree algorithm is applied to find out the classification rules, which help the government to make strategies to guard against foreign capital withdrawal.

关键词： motivation of the foreign capital withdrawal grey correlation degree decision tree algorithm

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Application of decision tree algorithm in Medical Nursing and Health Assessment System 3

Application of Decision Tree Algorithm in Medical Nursing an...

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3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)

作者： Mo, Hefeng Tao, Ting Gao, Wenbin Fan, Chunlei Wang, Ligang Zhao, Xin Wang, Haili Chinese Acad Sci Inst Psychol Key Lab Mental Hlth Beijing Peoples R China Univ Chinese Acad Sci Dept Psychol Beijing Peoples R China Wuxi City Maternal & Child Hlth Hosp Wuxi Peoples R China Shanghai Jiao Tong Univ Ruijin Hosp Sch Med Wuxi Branch Wuxi Peoples R China

ISBN: (纸本)9798350310801

In the rapid development of information construction of medical system, more and more work depends on information. Data mining can extract useful information hidden behind a large amount of information, so it is used more and more widely in hospital information construction. decision tree classification is an important method in data mining. decision tree mining technology is applied to medical and nursing and health data to analyze and mine the factors affecting medical and nursing staff's medical nursing and health. The medical nursing and health of medical staff is an important factor affecting their lives, work and safety. In recent years, they have received widespread attention at home and abroad. Therefore, it is urgent to evaluate the medical staff and provide health and psychological interventions to support this group. This paper studies the application of decision tree algorithm in the medical and nursing psychological personality health evaluation system, and understands the relevant theoretical knowledge of psychological evaluation on the basis of literature data, and then designs the medical nursing and health evaluation system based on the decision tree algorithm. The decision tree algorithm cited in the system is tested, and the test results show that after the improved algorithm in this paper is added with a balance coefficient of 0

关键词： decision tree algorithm Medical Nursing and Health Evaluation System Data Mining

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decision tree algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors

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JOURNAL OF STROKE & CEREBROVASCULAR DISEASES 2021年第4期30卷 105636-105636页

作者： Imura, Takeshi Iwamoto, Yuji Inagawa, Tetsuji Imada, Naoki Tanaka, Ryo Toda, Haruki Inoue, Yu Araki, Hayato Araki, Osamu Hiroshima Cosmopolitan Univ Fac Hlth Sci Dept Rehabil Hiroshima Japan Araki Neurosurg Hosp Dept Rehabil Hiroshima Japan Hiroshima Univ Grad Sch Humanities & Social Sci Hiroshima Japan Araki Neurosurg Hosp Dept Neurosurg Hiroshima Japan Natl Inst Adv Ind Sci & Technol Artificial Intelligence Res Ctr AIRC Tokyo Japan Kibi Int Univ Res Inst Hlth & Welf Okayama Japan

Background and purpose: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and environmental variables to identify stroke patients with a high possibility of home discharge. The present study aimed to identify the factors, including functional and environmental factors, affecting home discharge after stroke inpatient rehabilitation using the machine learning method. Method: This was a cohort study on data from the maintained database of all patients with stroke who were admitted to the convalescence rehabilitation ward of our facility. In total, 1125 stroke patients were investigated. We developed three classification and regression tree (CART) models to identify the possibility of home discharge after inpatient rehabilitation. Results: Among three models, CART model incorporating basic information, functional factor, and environmental factor variables achieved the highest accuracy for identification of home discharge. This model identified FIM dressing of the upper body (score of <2 or >2) as the first single discriminator for home discharge. Performing house renovation was associated with a high possibility of home discharge even in patients with stroke who had a poor FIM score in the ability to dress the upper body (<2) at admission into the convalescence rehabilitation ward. Interestingly, many patients who performed house renovation have achieved home discharge regardless of the degree of lower limb paralysis. Conclusion: We identified the influential factors for realizing home discharge using the decision tree algorithm, including environmental factors, in patients with convalescent stroke.

关键词： Stroke Home discharge Environmental factors decision tree algorithm

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A Study on Durian Selection Based on decision tree algorithm 7

A Study on Durian Selection Based on Decision Tree Algorithm

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7th International Conference on Electronic Information Technology and Computer Engineering (EITCE)

作者： Yang, Xiangdong Chen, Xiaoxin Guangzhou Huali Coll Sch Mech & Elect Engn Guangzhou 511325 Guangdong Peoples R China

ISBN: (纸本)9798400708305

Non-destructive classification of fruits based on the maturity stage is beneficial to the consumer and fruit industry. Improper ripening can lead to low eating quality and economic loss for the producers. Durian is known as the "King of Fruits" and is one of the rarest and sweetest fruits in South Asia. This study used decision tree algorithm in machine learning to analyze the dataset by assigning it to leaf nodes, thus enabling the prediction of selection of uncut durian. The results show the following conclusions: 1) The selection prediction of uncut durian was achieved by the decision tree algorithm model, which provides a rational decision-making reference for consumers. 2) The inference logic of the ID3 decision tree algorithm is intuitive, the interpretability is clear, and it is convenient for the visualization of the model. 3) The ID3 decision tree algorithm can not deal with attributes that have consecutive values, missing values, and it is inconvenient to deal with the consecutive features, and it is inclined to select the features with more values as split attributes, which may lead to overfitting.

关键词： decision tree algorithm Durian Selection Study

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Research on female talent recruitment system based on decision tree algorithm under the second-child policy

Research on female talent recruitment system based on decisi...

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International Conference on Big Data, Information and Computer Network (BDICN)

作者： Zhang, Jiayue Jamil, Rossilah Univ Teknol Malaysia Azman Hashim Int Business Sch Kuala Lumpur Malaysia

ISBN: (纸本)9781665484763

With the liberalization of the comprehensive second-child policy, the impact of fertility issues on womens employment has reappeared, causing widespread concern. The article introduces the current employment status and problems of women:women may extend the time to find a job due to the second child, or the professional continuity is not guaranteed, which will affect their career development,and then it explains the importance of the decision tree algorithm and how the decision tree algorithm is combined with the female talent recruitment system to help second-child women find suitable jobs as soon as possible and ease the competition in the talent market. Finally, it is concluded that the decision tree algorithm can make second-child women better understand which jobs they are more suitable for,and help second-child women master professional skills more quickly, learn more new knowledge, get more work challenges at work, let employees combine their own values and realize their own meaning in life.

关键词： Second child policy decision tree algorithm female talent recruitment system

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Prediction of Temperature for next three days using decision tree algorithm by comparing Sliding Window algorithm for better Accuracy 1

Prediction of Temperature for next three days using Decision...

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

作者： Yaswanth Reddy, G. Saravanan, M.S. Saveetha University Tamil Nadu Chennai602105 India

ISBN: (纸本)9781607685395

Aim: The aim of this study is to predict the temperature for the next three days using a machine learning algorithm and the objective of this research is to improve the accuracy of temperature prediction. Materials and methods: The study used 36 samples with two groups of algorithms with the g-power value of 80%. To predict the temperature the Sliding Window algorithm (SLA) machine learning algorithm has found 89% of accuracy and this study will find better accuracy for temperature prediction with the decision tree (DT) algorithm. Results: This research study found 92% of accuracy for temperature prediction using a DT algorithm. Conclusion: This study concludes that the DT algorithm on temperature prediction is significantly better than the SLA. © The Electrochemical Society

关键词： decision tree algorithm Innovative weather prediction Machine learning Sliding Window algorithm

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Application Research of College Student Employment Prediction Model Based on decision tree algorithm 3

Application Research of College Student Employment Predictio...

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3rd IEEE International Conference on Electrical Engineering, Big Data and algorithms, EEBDA 2024

作者： Yu, Miao Jilin Communications Polytechnic Jilin China

ISBN: (纸本)9798350380989

Employment is the cornerstone of people's livelihoods and plays a crucial role in economic development. In recent years, the scale of university enrollment has been continuously expanding, leading to a growing population of university graduates. In 2022, the total number of university graduates reached a historic high of 10.76 million, and the employment pressure on graduates has increased significantly, exacerbated by the impact of the COVID-19 pandemic. Therefore, it is of practical significance to apply effective analysis and prediction methods to understand employment trends. This article, based on the decision tree algorithm, establishes an employment prediction model using data related to university students' employment and academic performance, aiming to uncover key factors influencing student employment. The F-value of the employment prediction model constructed using the decision tree algorithm is 0.9026, indicating that the model performs well in predicting the employment status of university students. The results demonstrate that this model can accurately predict students' employment outcomes and identify influential factors including gender, ethnicity, graduation time, and academic performance. © 2024 IEEE.

关键词： decision tree algorithm employment prediction university graduates

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Hydroponic using Deep Water Culture for Lettuce Farming using Random Forest Compared with decision tree algorithm 8

Hydroponic using Deep Water Culture for Lettuce Farming usin...

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8th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Jegan, D. Surendran, R. Madhusundar, N. Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350367904

This research aims to optimize lettuce cultivation in a Deep Water Culture (DWC) hydroponic system by leveraging machine learning techniques. By analyzing various parameters such as temperature, pH, and nutrient concentration, the study seeks to identify optimal conditions for maximizing lettuce growth and yield. A Random Forest algorithm is employed to predict optimal parameter settings and compare its performance with a decision tree algorithm. The Random Forest's ensemble approach is expected to enhance prediction accuracy and robustness. By optimizing hydroponic parameters through machine learning, this research contributes to sustainable and efficient agriculture, reducing resource consumption and maximizing crop yield. © 2024 IEEE.

关键词： decision tree algorithm deep-water culture hydroponic lettuce farming random forest algorithm

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Research on Financial Irregularities of Listed Companies based on decision tree algorithm 3

Research on Financial Irregularities of Listed Companies bas...

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3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Xiao, Yuan Xiangnan University Hunan China

ISBN: (纸本)9798350317022

Violation of laws and regulations by listed companies is one of the main reasons for continuously disturbing China's securities market in recent years. How to effectively analyze and deal with violations of laws and regulations is an important topic in front of us. This paper makes use of the announcement disclosure and the China Securities Regulatory Commission and its local dispatched institutions Based on the regulatory punishment and punishment information publicly disclosed by Shanghai Stock Exchange and Shenzhen Stock Exchange, this paper analyzes the motivation and characteristics of illegal behaviors of listed companies, and obtains 14 main illegal behaviors. Then it uses the decision tree algorithm of data mining technology to analyze. The research on Financial Violations of listed according to decision tree approach is a systematic analysis method of information. Divide the data into different levels, and then analyze it using decision tree. The decision tree is used to find out whether there are any exceptions or inconsistencies in the data. Therefore, this study can be targeted at all types of financial violations, such as exaggerating profits and underreporting losses. © 2023 IEEE.

关键词： decision tree algorithm finance listed company violations

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Public Physical Education Teaching and Evaluation Analysis of College Students under decision tree algorithm 2

Public Physical Education Teaching and Evaluation Analysis o...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Wu, Gang Cui, Qun Jain, Amar Weifang Engineering Vocational College China Department of Civil Engineering Pune India

ISBN: (纸本)9798350317558

With the promotion of Healthy China Strategy and the popularization of national fitness, the position of physical education in higher education has been paid more and more attention. This paper analyzes the current situation of college students' public physical education by means of literature, questionnaire and other research methods, and puts forward the corresponding reform countermeasures, aiming at improving the teaching quality and enhancing students' physical quality and health level © 2024 IEEE.

关键词： computer technology decision tree algorithm Pedagogical evaluation public physical education for university students

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