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Path Planning algorithm and id3 Decision Tree Model Application of Scenic Intelligent Navigation System

Procedia Computer Science 2024年 247卷 1187-1196页

作者： Ming Qiu Collegeof Tourism Bohai University Jinzhou China

The assumption space of id3 algorithm contains all decision trees, and the search space is also a complete assumption space. The current assumptions based on the information gain standard, and uses the information gain to reduce the sensitivity to individual training sample errors. Based on id3 decision tree algorithm, this paper provides new ideas and methods for the quality optimization of tourist attractions. Firstly, id3 decision tree algorithm model is constructed based on information entropy theory; Then, based on the literature research and system research methods, the quality evaluation indicator system of tourist attractions is constructed; Finally, based on the mathematical model and evaluation indicator system, the empirical research was carried out, and the data of 17 tourist attractions were collected. The expected research results were obtained according to the data preprocessing, data calculation process, decision tree construction and rule generation process. The research finds that the quality evaluation process of tourist attractions based on id3 decision tree model, through data preprocessing, data calculation, decision tree construction and decision rules generation, etc. it can be concluded that the "Tourism environment quality" attribute is the most important in this evaluation system, and "Tourism landscape quality" is relatively important. Tourist attractions can improve the work and quality of tourist attractions according to the research results.

关键词： id3 algorithm qualityevaluation mathematical model indicator system empirical research

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An Improved id3 Decision Tree algorithm Based on Attribute Weighted

An Improved ID3 Decision Tree Algorithm Based on Attribute W...

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2015 2nd International Conference on Civil,Materials and Environmental Sciences(CMES 2015)

作者： Xian Liang Fuheng Qu Yong Yang Hua Cai College of Computer Science and Technology Changchun University of Science and Technology College of electronic and information engineering Changchun University of Science and Technology

id3 decision tree algorithm uses information gain selection splitting attribute tend to choose the more property values, and the number of attribute values can not be used to measure the attribute importance, in view of the above problems, a new method is proposed for attribute weighting, the idea of simulation conditional probability, calculation of the close contact between the attributes and the decision attributes, as the attribute weights and combination with attribute information gain to selection splitting attribute, improve the accuracy of decision results. Experiments show that compared with the improved algorithm and the traditional id3 algorithm, decision tree model has higher predictive accuracy, less number of leaves.

关键词： decision tree id3 algorithm information gain

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Predicting the Early Sign of Diabetes using id3 as a Data Model 14

Predicting the Early Sign of Diabetes using ID3 as a Data Mo...

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14th International Conference on Computer and Automation Engineering (ICCAE)

作者： Lagunzad, Herminino C. Impang, Maria Aura C. Gonzaga, Mikee, V Lawan, Joan F. Pineda, Fernandez C. Tanjente, Rose Anne A. Quezon City Univ Coll Comp Sci & Informat Technol Quezon City Philippines

ISBN: (纸本)9781665483797

We all know that diabetes is a very chronic disease that needs to be detected in the early stage so we can prevent this. Detecting it in the early stage can help us to treat it well and improve treatment. Also, data mining techniques had been used in doing this research to analyze the data and to predict the output. With this paper, the researchers managed to use the id3 algorithm as a data model that will need those attributes, test datasets, and training datasets for us to predict if the patient is diabetic or not. The medical professional may benefit from this since the application can perform a bundle of tests for multiple patients for easily identifying if the patient is diabetic or not. If the patient is diabetic, it can treat in the early stage.

关键词： Data Mining Diabetes id3 algorithm

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Decision trees in selection of featured determined food quality

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ANALYTICA CHIMICA ACTA 2011年第1-2期705卷 261-271页

作者： Debska, B. Guzowska-Swider, B. Rzeszow Univ Technol Dept Comp Chem PL-35041 Rzeszow Poland

The determination of food quality, authenticity and the detection of adulterations are problems of increasing importance in food chemistry. Recently, chemometric classification techniques and pattern recognition analysis methods for wine and other alcoholic beverages have received great attention and have been largely used. Beer is a complex mixture of components: on one hand a volatile fraction, which is responsible for its aroma, and on the other hand, a non-volatile fraction or extract consisting of a great variety of substances with distinct characteristics. The aim of this study was to consider parameters which contribute to beer differentiation according to the quality grade. Chemical (e.g. pH, acidity, dry extract, alcohol content, CO2 content) and sensory features (e.g. bitter taste, color) were determined in 70 beer samples and used as variables in decision tree techniques. This pattern recognition techniques applied to the dataset were able to extract information useful in obtaining a satisfactory classification of beer samples according to their quality grade. Feature selection procedures indicated which features are the most discriminating for classification. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Principal component analysis id3 algorithm Decision tree Classification Feature selection

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Research on art innovation teaching platform based on data mining algorithm

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第6期22卷 14943-14949页

作者： Long, Yinjiao Wuchang Univ Technol Sch Environm & Art Design Wuhan Hubei Peoples R China

The attention paid to art teaching is not greatly increased, and the Ministry of Education also formulates corresponding exercises and standards of achievement according to the education curriculum. Under this condition, the data mining technology is applied to the process of art achievement evaluation. First of all, the id3 algorithm of the decision tree is built which is obtained by the art test scores mining, and then the data flow is combined in the algorithm. In addition, in connection with the student's own artistic achievements, the algorithm is tested and the data mining analysis is conducted to finally obtain the students. The characteristic information and the algorithm indicates that the text have practicability, which has a certain positive effect on art education in colleges and universities.

关键词： Data mining Art innovation teaching id3 algorithm

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A novel feature-selection approach based on the cuttlefish optimization algorithm for intrusion detection systems

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第5期42卷 2670-2679页

作者： Eesa, Adel Sabry Orman, Zeynep Brifcani, Adnan Mohsin Abdulazeez Zakho Univ Dept Comp Sci Fac Sci Duhok City Krg Iraq Istanbul Univ Dept Comp Engn Fac Engn TR-34320 Istanbul Turkey Duhok Polytech Univ Dept IT Duhok Tech Inst Duhok City Krg Iraq

This paper presents a new feature-selection approach based on the cuttlefish optimization algorithm which is used for intrusion detection systems (idSs). Because idSs deal with a large amount of data, one of the crucial tasks of idSs is to keep the best quality of features that represent the whole data and remove the redundant and irrelevant features. The proposed model uses the cuttlefish algorithm (CFA) as a search strategy to ascertain the optimal subset of features and the decision tree (DT) classifier as a judgement on the selected features that are produced by the CFA. The KDD Cup 99 dataset is used to evaluate the proposed model. The results show that the feature subset obtained by using CFA gives a higher detection rate and accuracy rate with a lower false alarm rate, when compared with the obtained results using all features. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Feature selection Cuttlefish algorithm Intrusion detection systems Decision trees id3 algorithm

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COMPARISON OF KNOWLEDGE ELICITATION TECHNIQUES IN THE DOMAIN OF ELECTRONIC FILTER TUNING

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IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING 1990年第5期137卷 337-344页

作者： TSAPTSINOS, D MIRZAI, AR JERVIS, BW COWAN, CFN UNIV EDINBURGH DEPT ELECT ENGNEDINBURGH EH9 3JLMIDLOTHIANSCOTLAND

The work done towards the construction of an expert system to assist an operator in the identification of the corrective action to be applied during tuning of electronic filters is described. The first part of the paper introduces two algorithms for induction by examples (id3 and adaptive combiner) and their relationship to expert systems. The two algorithms were applied, in a series of tests which involved an incremental presentation of a number of examples, to the task of filter tuning. The reported results suggest the use of id3 when a small number of classes is present. The second part of the paper presents subsequent work with id3. Results are reported of using this algorithm for filter tuning with examples containing either numerical or logical attribute values. A comparison of the results showed that improved test performance was achieved by using logical values.

关键词： Electronic engineering computing electronic filter tuning Expert systems and other AI software and techniques knowledge acquisition test performance band-pass filters bandpass crystal filters adaptive combiner crystal filters expert systems attribute values knowledge elicitation techniques id3 algorithm Passive filters and other passive networks tuning

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Information classification algorithm based on decision tree optimization

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第3期22卷 S7559-S7568页

作者： Wang, Hongbin Wang, Tong Zhou, Yucai Zhou, Lianke Li, Huafeng Harbin Engn Univ Coll Comp Sci & Technol Harbin Heilongjiang Peoples R China Harbin Engn Univ Informat & Commun Engn Coll Harbin Heilongjiang Peoples R China Changsha Univ Sci & Technol Sch Energy & Power Changsha 410076 Hunan Peoples R China

With the rapid development of information technology, the efficiency of information management has drawn increasing importance with its broadening application. Hence, a new information classification algorithm has proposed in this paper so as to improve information management of the limited resources by reducing its complexity. However, id3 algorithm is a classical and imprecise algorithm in data mining, because traditional id3 algorithm selects the attribute that has the maximum information gain according to the data set as that of the split node. Then the data subset is further divided according to the number of attribute values, and the information gain of each subset is calculated recursively. Decision Tree Optimization Ratio is the core approach in this algorithm, whose basic ideas have been introduced and analysed, proving to be more complex. Therefore, the authors propose a relatively precise RLBOR algorithm which takes the number of nodes in the decision tree model into consideration. The experiment show more precise of RLBOR algorithm.

关键词： id3 algorithm Decision tree model Decision tree optimization ratio Leaf nodes

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Approach to Anomaly Traffic Detection in a Local Network

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Journal of Donghua University(English Edition) 2009年第6期26卷 656-661页

作者：王秀英肖立中邵志清 Department of Computer Information Shanghai Xinqiao Vocational and Technical College School of Information Science and Engineering East China University of Science and Technology Department of Computer Science and Information Engineeting Shanghai Institute of Technology

The research intends to solve the problem of the occupation of bandwidth of local network by abnormal traffic which affects normal user's network ***,a new algorithm in this paper named danger-theory-based abnormal traffic detection was *** an advanced id3 algorithm was presented to classify the abnormal *** a new model of anomaly traffic detection was built upon the two algorithms above and the detection results were integrated with *** firewall limits the bandwidth based on different types of abnormal *** show the outstanding performance of the proposed approach in real-time property,high detection rate,and unsupervised learning.

关键词： clanger theory information enlropy id3 algorithm abnormal traffic

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A DECISION MODEL OF idENTIFYING USER TRAVEL PATTERN BASED ON THE INTELLIGENT TERMINAL SENSOR DATA 4

A DECISION MODEL OF IDENTIFYING USER TRAVEL PATTERN BASED ON...

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4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Wang, Shuai Xiu, Jiapeng Liu, Chen Yang, Zhengqiu Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

ISBN: (纸本)9781509012565

The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern decision model based on the sensor data. The decision algorithm adopts decision tree algorithm based on id3. Experiments data shows that this decision model is effective in identifying the pattern of user's travel.

关键词： User travel Pattern Sensor Data Travel pattern identifying Decision tree id3 algorithm

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