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2012 IEEE 14th International Conference on Communication Technology

作者： Manish Kumar M.Hanumanthappa T.V.Suresh Kumar Dept.of Master of Computer Applications M.S.Ramaiah Institute of Technology Research Scholar Department of Computers Science and ApplicationsBangalore University Dept.of Computer Science and Applications Jnana Bharathi CampusBangalore University

Intrusion Detection System (IDS) is the most powerful system that can handle the intrusions of the computer environments by triggering alerts to make the analysts take actions to stop this ***’s are based on the belief that an intruder’s behavior will be noticeably different from that of a legitimate user.A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious attacks by using traditional statistical methods to new data mining approaches in last ***,today's commercially available intrusion detection systems are signature- based that are not capable of detecting unknown *** this paper we analyze a classification model for misuse and anomaly attack detection using decision tree algorithm.

关键词： Intrusion Detection System KDD Dataset Network Security decision tree algorithm

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Analysis of Transmission Route of MERS Coronavirus Using decision tree and Apriori algorithm 18

Analysis of Transmission Route of MERS Coronavirus Using Dec...

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18th International Conference on Advanced Communication Technology (ICACT)

作者： Kim, Donghyun Hong, Soyoung Choi, Sungwoo Yoon, Taeseon Hankuk Acad Foreign Studies Nat Sci Yongin South Korea Hankuk Acad Foreign Studies Fac Comp Yongin South Korea

ISBN: (纸本)9788996865063

Middle East Respiratory Syndrome, which is a respiratory disease caused by MERS coronavirus, is known to be an endemic disease spread in Kingdom of Saudi Arabia, or KSA. On May 20, 2015, it has massively occurred in Republic of Korea, with 186 confirmed cases, 36 deaths. In this paper, we analyzed sonic features of MERS-CoV's transmission route by a new molecular approach. We have collected DNA sequences of MERS-CoV from 15 different regions in the world, including some regions of KSA. We have converted the DNA sequences into amino acid sequences and used Apriori and decision tree algorithm to found the similarities and differences between different MERS-CoVs' amino acid sequences. Then, we drew some conclusions about MERS's transmission routes by using these results.

关键词： Middle East Respiratory Syndrome MERS Apriori decision tree algorithm transmission route epidemiological investigation

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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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Comparison of Flavivirus Using Datamining-Apriori, K-means, and decision tree algorithm

Comparison of Flavivirus Using Datamining-Apriori, K-means, ...

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International Conference on Advanced Communication Technology

作者： Chan woo Kim Se Hwan Ahn Taeseon Yoon Natural Science Hankuk Academy of foreign studies Yong-in Republic of Korea Computer Science and Engineering Korea University Seoul Republic of Korea

ISBN: (纸本)9781509048922

Nowadays, zika virus infection-occurred in brazil-is becoming serious global problem. Temporary treatments-using drug-can alleviate symptoms for a while but cannot be a basic solution for infections. We researched amino acids of Zika virus and other four kinds of flaviviruses-Dengue fever, Yellow fever, Saint Louis, Japanese Encephalitis-with bioinformatic experiment;Apriori, K-means and decision tree algorithm. Results show differences and common things among them-Japanese Encephalitis has most representative amino acid.

关键词： zika virus and flavivirus genetic treatment apriori k-means decision tree algorithm

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An Applied Research of decision tree algorithm in Track and Field Equipment Training

An Applied Research of Decision Tree Algorithm in Track and ...

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The 2015 International Conference on Energy,Materials and Manufacturing Engineering(EMMS 2015)

作者： Shaoqing Liu Kebin Wang Teaching and Research Office of Physical Education Department of Public Basic CoursesLangfang Health Vocational College Langfang Health Vocational College

ISBN: (纸本)9781510814585;1510814582

This paper has conducted a study on the applications of track and field equipment training based on ID3 algorithm of decision tree *** the selection of the elements used by decision tree,this paper can be divided into track training equipment,field events training equipment and auxiliary training equipment according to the properties of track and field *** decision tree that regards track training equipment as root nodes has been obtained under the conditions of lowering computation cost through the selection of data as well as the application and optimization of ID3 algorithm model.

关键词： decision tree algorithm track and field equipment training auxiliary training equipment

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Analysis of Transmission Route of MERS Coronavirus Using decision tree and Apriori algorithm

Analysis of Transmission Route of MERS Coronavirus Using Dec...

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International Conference on Advanced Communication Technology

作者： Donghyun Kim Soyoung Hong Sungwoo Choi Taeseon Yoon Natural Science: Hankuk Academy of Foreign Studies Yongin Republic of Korea Faculty of Computer: Hankuk Academy of Foreign Studies Yongin Republic of Korea

ISBN: (纸本)9781509016969

Middle East Respiratory Syndrome, which is a respiratory disease caused by MERS coronavirus, is known to be an endemic disease spread in Kingdom of Saudi Arabia, or KSA. On May 20, 2015, it has massively occurred in Republic of Korea, with 186 confirmed cases, 36 deaths. In this paper, we analyzed some features of MERS-CoV's transmission route by a new molecular approach. We have collected DNA sequences of MERS-CoV from 15 different regions in the world, including some regions of KSA. We have converted the DNA sequences into amino acid sequences and used Apriori and decision tree algorithm to found the similarities and differences between different MERS-CoVs' amino acid sequences. Then, we drew some conclusions about MERS's transmission routes by using these results.

关键词： Middle East Respiratory Syndrome MERS Apriori decision tree algorithm transmission route epidemiological investigation

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decision tree analysis of cutter selection for tunnel boring machines: A study of geological conditions and machine types in high-performing TBM projects

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2025年 162卷

作者： Farrokh, Ebrahim Lotfi, Davood Amirkabir Univ Technol Tehran Polytech Tehran Iran Tunnel Saz Machine Co R&D Div Tehran Iran

The selection of appropriate cutter types and configurations is crucial for effective Tunnel Boring Machine (TBM) operations. This study introduces a novel decision tree methodology to develop a model for selecting primary cutter types (PCT) and cutter configurations based on actual data from 112 high-performing TBM projects. Key parameters, including geological conditions (Soft Soil, Hard Soil, Coarse Soil, Bouldery Ground, Soft Mixed, Hard Mixed), machine type, diameter, and cutter type, were analyzed. Various decision tree algorithms, including C4.5, CART, SVM, Random Forest, and ensemble methods such as Bagging, AdaBoost, XGBoost, and LightGBM, were applied and evaluated using performance metrics (accuracy, precision, recall, F1-score, and ROC-AUC). Results indicate that CART and KNN algorithms are the best performers, with accuracies of 89.3 % and 88.4 %, respectively, while AdaBoost was the least effective. decision rules from the CART model reveal geological conditions as the most significant predictor of PCT, followed by machine type and diameter. This study provides a systematic framework for cutter configuration selection in mechanized tunneling, offering practical guidelines for the industry.

关键词： TBM Cutter selection decision tree algorithm Geological conditions Cutter configuration

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decision tree algorithms for image data type identification

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LOGIC JOURNAL OF THE IGPL 2017年第1期25卷 67-82页

作者： Khoa Nguyen Dat Tran Ma, Wanli Sharma, Dharmendra Univ Canberra Fac Educ Sci Technol & Math Canberra ACT 2601 Australia

Identifying file type of file fragments has been investigated for a long time but it is still a challenge. It is found in the literature that high-entropy file fragments make the problem more complicated. Especially, existing popular file types share same compression algorithms such as deflate algorithm that causes file type identification for file fragment become harder. Applying machine learning or empirical techniques is to deal with this problem. Compression algorithms are used to reduce the size of files that have big data size and include image files. Many research work of file type identification have been done for JPEG format, and the Rate of Change feature is proven to work effectively for it. Conversely, few efforts have been made for PNG although this is a popular image format and widely used nowadays. In this article, we propose a new approach based on the deflate-encoded data detection, entropy-based clustering, and decision tree techniques to identify PNG data fragments which are the deflate-encoded fragments. Experiments showed high accuracy rates for the proposed method.

关键词： File fragment identification image data type identification PNG SVM decision tree algorithm Shannon entropy

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Predicting slump for high-performance concrete using decision tree and support vector regression approaches coupled with phasor particle swarm optimization algorithm

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STRUCTURAL CONCRETE 2024年第5期25卷 4103-4118页

作者： Sun, Qingmei Gongping, Yu Zhejiang Guangsha Vocat & Tech Univ construct Dongyang 322100 Zhejiang Peoples R China Zhongtian Construct Grp Co Ltd Hangzhou 310002 Peoples R China

The main focus of this study is to assess the slump characteristics of high-performance concrete (HPC) using decision tree (DT) and support vector regression (SVR) models. In the first step, the models were solely fed via HPC samples to reproduce the slump rates. By coupling phasor particle swarm optimization (PPSO) to main models, hybrid DT-PPSO and SVR-PPSO frameworks, simulate the slump rates accurately. Using the correlation of determination and root mean square error (MAE) metrics for the DT, 96.04 and 5.097 were computed, respectively. SVR was obtained at 92.62 and 6.965, alternatively. In the hybrid approach, DT-PPSO could improve by 3% and 55% in terms of correlation of determination and root MAE, respectively. DT-PPSO appeared high-accuracy model compared to others;however, a single DT had more desirable results than SVR. Overall, the advantages of this study encompass its methodological approach, comparative insights, and practical relevance, offering valuable contributions to the understanding and prediction of mechanical slump in HPC.

关键词： decision tree algorithm high-performance concrete compressive strength phasor particle swarm optimization slump support vector regression

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Heart Disease Prediction System Using decision tree and Naive Bayes algorithm

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CURRENT MEDICAL IMAGING 2019年第8期15卷 712-717页

作者： Maheswari, Subburaj Pitchai, Ramu Natl Engn Coll Dept Comp Sci & Engn Kovilpatti 628503 Tamil Nadu India BV Raju Inst Technol Dept Comp Sci & Engn Narsapur 502313 Telangana India

The huge information of healthcare data is collected from the healthcare industry which is not "mined" unfortunately to make effective decision making for the identification of hidden information. The end user support system is used as the prediction application for the heart disease and this paper proposes windows through the intelligent prediction system the instance guidance for the heart disease is given to the user. Various symptoms of the heart diseases are fed into the application. The user precedes the processes by checking the specific detail and symptoms of the heart disease. The decision tree (ID3) and navie Hayes techniques in data mining are used to retrieve the details associated with each patient. Based on the accurate result prediction, the performance of the system is analyzed.

关键词： Intelligent prediction system decision tree algorithm knowledge representation data mining naive bayes algorithm heart disease prediction

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