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College public sports culture practice based on decision tree algorithm

PERSONAL AND UBIQUITOUS COMPUTING 2020年第2期24卷 207-221页

作者： Xu, Shuping Liang, Lixin Ji, Chengbin North China Elect Power Univ Beijing 102206 Peoples R China Beijing Coll Polit & Law Beijing 102628 Peoples R China

The public sports culture of colleges is based on the basic skills and strategies of the public sports culture curriculum. The study of public sports culture in colleges focuses on the unity and standardization of teaching forms, structures, contents, methods, assessments, and evaluations. This paper considers the various links that affect the public sports culture of colleges, identifies frequent item sets, and gains support by establishing support and confidence thresholds. The frequent item sets of the degrees and confidence with the rules generated by a decision tree algorithm are compared to identify the key factors that affect the actual effect. This paper fully considers the public sports culture of colleges to comprehensively analyze the relevant factors, verify and compare the rules generated by the decision tree algorithm, and identify the key factors that affect the actual effect. By an example verification, the method of this paper has certain guiding value for the study of public sports culture.

关键词： Frequent item sets decision tree algorithm Public sports culture

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A decision tree algorithm for forest fire prediction based on wireless sensor networks

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INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS 2020年第4期13卷 422-430页

作者： Gao, Demin Xin, Jie Zhang, Fuquan Nanjing Forestry Univ Coll Informat Sci & Technol Nanjing 210037 Peoples R China Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA McMaster Univ Elect & Comp Engn Dept Hamilton ON Canada

Forest fire poses a significant threat not only to the natural environment and ecological systems but also to the safety of human life and property. Combined with new technologies, a decision tree algorithm is proposed for forest fire prediction, in which wireless sensor networks technology is utilised to transmit data and predict the ignition of the forest. There are four meteorological parameters as part of training data, containing temperature, relative humidity, wind speed, and daily precipitation, while the other part is prediction results of Forest Weather Index system. The decision tree generated by our system could classify these parameters from the most significant to the least significant so that it can better foretell fire occurrence. The analysis of prediction results shows that our system is effective.

关键词： decision tree algorithm forest fire prediction wireless sensor networks WSNs

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Taguchi approach and decision tree algorithm for prediction of wear rate in zinc oxide-filled AA7075 matrix composites

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SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES 2021年第3期9卷 035005-035005页

作者： Alagarsamy, S., V Balasundaram, R. Ravichandran, M. Mohanavel, V Karthick, Alagar Devi, S. Sathiya Mahath Amma Inst Engn & Technol Dept Mech Engn Pudukkottai 622101 Tamil Nadu India K Ramakrishnan Coll Engn Dept Mech Engn Tiruchirappalli 621112 Tamil Nadu India Bharath Inst Higher Educ & Res Ctr Mat Engn & Regenerat Med Chennai 600073 Tamil Nadu India KPR Inst Engn & Technol Dept Elect & Elect Engn Coimbatore 641407 Tamil Nadu India Univ Coll Engn Dept Comp Sci Engn Bit Campus Tiruchirappalli 620024 Tamil Nadu India

This work aims to apply data-driven approach [decision tree (DT) algorithm] to analyse the wear rate (WR) of ZnO-filled AA7075 composites. The results of model-based analysis was compared with Taguchi analysis. Stir casting was used to produce the composite samples. Characterization studies were conducted to analyse the composition and morphology. The scanning electron microscopy results indicated the even dispersion of ZnO in the AA7075. The energy-dispersive x-ray spectroscopy pattern ensures the presence of matrix elements and the inclusion of reinforcement particles into the proposed composites. To minimize the number of experimentation, L27 Orthogonal array is used for finding WR. The 'DuCom' Pin-on-Disc apparatus were used to prepare WR data for the set of the proposed composites. Taguchi technique reveals the optimum level factors for obtaining the minimum 'WR' is reinforcement content of 10 wt.%, applied load (P) at 10 N, sliding velocity (V) at 1 m s(-1) and sliding distance (D) of 1000 m. The experiments results from DT algorithm, and analysis of variance and signal-to-noise ratio analysis from Taguchi-based approach confirmed that reinforcement is the primary element for affecting wear of the composites. The reason for applying DT algorithm is that, the low-level knowledge could be converted into high-level knowledge (If-then-else rules), which can be effortlessly explicable by semiskilled personnel.

关键词： composites aluminium alloy zinc oxide wear rate optimization taguchi method decision tree algorithm

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Application of decision tree Intelligent algorithm in Mathematical Modeling Structure of Automation Control 1

Application of Decision Tree Intelligent Algorithm in Mathem...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Mou, Jiazheng Jiangsu Jari Information Technology Co. Jiangsu Lianyungang China

ISBN: (纸本)9798350316469

In order to establish a delay automatic control model with lower control error and better reduction of uplink load, based on existing work, this paper adopted decision tree intelligent algorithm to mathematically model the automatic control. Based on this, this article studied the collaborative scheduling mechanism of decision tree intelligent algorithms and the collaborative scheduling of resources. Firstly, this article analyzed the delay uncertainty in the communication process and adopted a probability graph based method to simplify the probability model composed of delay uncertainty, thereby improving the efficiency of delay automatic control. Next, this article explored an online learning method based on decision tree intelligent algorithms to simplify probability models and model them mathematically. Finally, the communication characteristics of the decision tree intelligent algorithm were simulated and control experiments were conducted on the proposed scheme. The experimental results showed that the CART algorithm achieved the best classification results on the four evaluation indicators of F-Measure, G-Mean, AUROC (Area Under the Receiver Operating Characteristic), and AUPRC (Area Under the Precision Recall Curve) of the diagnostic model for the test dataset established using different modeling methods, with values of 0.92, 0.894, 0.907, and 0.9, respectively. © 2023 IEEE.

关键词： decision tree algorithm ID3 algorithm Information Increment Mathematical Modeling

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EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH decision tree algorithm

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SURFACE REVIEW AND LETTERS 2021年第4期28卷 2150021-2150021页

作者： Raveendran, P. Alagarsamy, S. V. Ravichandran, M. Meignanamoorthy, M. Mahath Amma Inst Engn & Technol Dept Mech Engn Pudukkottai 622101 Tamil Nadu India K Ramakrishnan Coll Engn Dept Mech Engn Tiruchirappalli 621112 Tamil Nadu India

The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed (V), feed (F), and depth of cut (D) on surface roughness (Ra) of turning AA7075 filled with 10wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner within the matrix material. The machining of composite was carried out by using the CNC turning center and tungsten carbide insert as tool material. This experimental work was designed on L27 (3(3)) orthogonal array using Taguchi's design of experiments. From its signal-to-noise (S/N) ratio study, the minimum surface roughness (Ra) was obtained at the optimum level of parameters with the cutting speed at 1500rpm, feed at 0.15mm/rev and depth of cut at 0.3mm. Analysis of variance (ANOVA) and decision tree (DT) algorithm were used to identify the significant effect of parameters. The experimental result shows that depth of cut was the major significant parameter on surface roughness (Ra) when compared to cutting speed and feed.

关键词： AA7075 TiO2 CNC turning surface roughness taguchi method ANOVA decision tree algorithm

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DEVELOPMENT OF STATISTICAL BASED decision tree algorithm FOR MIXED CLASS CLASSIFICATION WITH SENTINEL-2 DATA

DEVELOPMENT OF STATISTICAL BASED DECISION TREE ALGORITHM FOR...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Singh, Vatsala Singh, K. P. Mody Univ Sci & Technol Laxmangarh Rajasthan India Bananas Hindu Univ Indian Inst Technol Dept Elect Engn Varanasi 221005 Uttar Pradesh India

ISBN: (纸本)9781728163741

Nowadays various types of satellite data are available which have different spectral bands. These spectral bands have special characteristics to interact with particular targets. Therefore, it is also important to use these bands efficiently. The prime objective of this paper is to identify the various land cover classes namely bare soil, moist soil, urban, tall vegetation, short vegetation, pasture, water with sentinel-2 data. The task takes up a challenging edge because various classes among the aforementioned list have characteristic similarities making it cumbersome to classify them effectively with different bands of sentinel-2 data. The classes like urban and bare soil, short vegetation and pasture, tall vegetation and short vegetation, moist soil and bare soil have similarities in their respective characteristics in different bands of the sentinel-2 and are often referred as mixed classes. For this purpose, 10 bands of sentinel-2 were used and results were compared with commonly used techniques like support vector machine. It is observed that the proposed statistical based decision tree algorithm with 10 bands of sentinel-2 has good capability to segregate pastures and moist soil as well as other classes with good accuracy.

关键词： decision tree algorithm Sentinel-2 SVM

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Analysis of Public Physical Education Teaching and Quality Evaluation in Colleges and Universities Based on decision tree algorithm 2020

Analysis of Public Physical Education Teaching and Quality E...

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2020 2nd International Workshop on Artificial Intelligence and Education

作者： Xia Huang Jianghan University China

ISBN: (纸本)9781450388252

Physical education in the past teaching field is relatively low, which leads to the physical quality of many modern students is relatively weak, and physical quality is related to the health of students and whether learning activities can be carried out smoothly. Therefore, modern colleges and universities pay more attention to physical education teaching and carry out public physical education courses. However, public physical education curriculum has its own quality requirements. If the quality is not up to the standard, it can not guarantee the students' physical quality. At this time, it is necessary to evaluate the teaching and quality of Public Physical Education in Colleges and universities. This paper puts forward a teaching and quality evaluation scheme based on decision tree algorithm, and uses methods to evaluate the teaching and quality of Public Physical Education in a university. The results show that the scheme is effective.

关键词： decision tree algorithm teaching quality evaluation college public physical education

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Pedestrian Crossing Safety System at Traffic Lights based on decision tree algorithm

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2019年第8期10卷 375-379页

作者： Hardiyanto, Denny Rojali, Muamar Iswanto Sartika, Dyah Anggun AKPRIND Yogyakarta Inst Sains & Teknol Dept Elect Engn Yogyakarta Indonesia Univ Muhammadiyah Yogyakarta Dept Elect Engn Yogyakarta Indonesia Politeknik Negeri Madiun Dept Comp Control Engn Madiun Indonesia

Pedestrians are one of the street users who have the right to get priority on security. Highway users such as vehicle drivers sometimes violate the traffic lights that is endanger pedestrians and make pedestrians feel insecure when crossing the street. Based on this problem, a tool is designed to provide a warning for the drivers or riders violating the traffic lights and prevent traffic accident by spraying water. The system is able to detect traffic violation based on changes in the value of the vehicle position on the stop line obtained from the Ultrasonic HC-SR04 sensor. When a violation is detected, a decision tree algorithm turns on the pump to spray water to the traffic violators as a deterrent effect. The results show that the vehicle located closest to the sensor has 94% precision, 88% recall and 85% accuracy, the vehicle located in the middle has 73% precision, 100% recall, and 75% accuracy, and the vehicle located furthest to the sensor has 75% precision, 100% recall and 80% accuracy.

关键词： Pedestrian safety decision tree algorithm traffic light spraying water

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Mortality prediction and long-term outcomes for civilian cerebral gunshot wounds: A decision-tree algorithm based on a single trauma center

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JOURNAL OF CLINICAL NEUROSCIENCE 2020年第0期75卷 71-79页

作者： Kim, Lily H. Quon, Jennifer L. Cage, Tene A. Lee, Marco B. Lan Pham Singh, Harminder Stanford Univ Dept Neurosurg Sch Med 300 Pasteur Dr Stanford CA 94305 USA Santa Clara Valley Med Ctr 751 S Bascom Ave San Jose CA 95128 USA

Gunshot wounds (GSW) are one of the most lethal forms of head trauma. The lack of clear guidelines for civilian GSW complicates surgical management. We aimed to develop a decision-tree algorithm for mortality prediction and report long-term outcomes on survivors based on 15-year data from our level 1 trauma center. We retrospectively reviewed 96 consecutive patients who presented with cerebral GSWs between 2003 and 2018. Clinical information from our trauma database, EMR, and relevant imaging scans was reviewed. A decision-tree model was constructed based on variables showing significant differences between survivors and non-survivors. After excluding patients who died at arrival, 54 patients with radiologically confirmed intracranial injury were included. Compared to survivors (51.9%), non-survivors (48.1%) were significantly more likely to have perforating (entry and exit wound), as opposed to penetrating (entry wound only), injuries. Bi-hemispheric and posterior fossa involvement, cerebral herniation, and intraventricular hemorrhage were more commonly present in non-survivors. Based on the decision-tree, Glasgow Coma Scale (GCS) > 8 and penetrating, uni-hemispheric injury predicted survival. Among patients with GCS <= 8 and normal pupillary response, lack of 1) posterior fossa involvement, 2) cerebral herniation, 3) bi-hemispheric injury, and 4) intraventricular hemorrhage, were associated with survival. Favorable long-term outcomes (mean follow-up 34.4 months) were possible for survivors who required neurosurgery and stable patients who were conservatively managed. We applied clinical and radiological characteristics that predicted survival to construct a decision-tree to facilitate surgical decision-making for GSW. Further validation of the algorithm in a large patient setting is recommended. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Gunshot wound Traumatic brain injury decision tree algorithm Mortality outcome

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Financial Management and decision Based on decision tree algorithm

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WIRELESS PERSONAL COMMUNICATIONS 2018年第4期102卷 2869-2884页

作者： Jin, Maozhu Wang, Hua Zhang, Qian Luo, Cheng Sichuan Univ Sch Business Chengdu Sichuan Peoples R China Chengdu Agr Coll Econ & Management Sch Chengdu 610064 Sichuan Peoples R China

In order to make university financial management more scientific, technologies such as data warehouse, data mining technology and decision support system are applied to college affairs decision-making. Aimed at a large amount of financial data generated by the financial management system in colleges and universities, the financial management and decision-making in colleges and universities are realized based on the decision tree algorithm. It provides effective support for the management of colleges and universities. The advantages and disadvantages of clustering algorithm and classification algorithm are analyzed. An improved C4.5 decision tree algorithm based on metric is proposed. Combined with data warehouse, data mining and analysis technology, data-driven thinking is adopted to establish university financial budget and model. Financial management and decision-making in colleges and universities are realized. It is applied to the financial project budget execution progress early warning, and carries on the experiment analysis and the result research. A complete financial data warehouse is built. Data aggregation, data analysis and data mining can reduce the amount of data information of the system. The result shows that this method makes college financial management and decision-making more convenient and effective.

关键词： University Financial management Data mining Data analysis decision tree algorithm

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