Application of C4.5 Algorithm in Evaluation of Railway Large Maintenance Machinery Construction

2014 ◽  
Vol 496-500 ◽  
pp. 1770-1773
Author(s):  
Wei Qiao Zhu ◽  
Tian Yun Shi
Keyword(s):  
Decision Tree ◽  
Training Sample ◽  
Important Research ◽  
Machinery Construction ◽  
Railway Infrastructure ◽  
Tree Modeling ◽  
Sample Data ◽  
C4.5 Algorithm ◽  
Evaluation Decision ◽  
Infrastructure Maintenance

With improvement of the level of modernization and mechanization of railway infrastructure maintenance, Railway large maintenance machinery (RLMM) is considered to be one of the main equipment. We have accumulated large amounts of RLMM construction data. How to mine valuable information from these data has become an important research subject. The C4.5 algorithm of decision tree is a useful method of data mining and classification. The paper solves evaluation of RLMM construction problem based on the C4.5 algorithm. By means of extracting the attribute with maximum gain ratio as the root node of the decision tree from training sample data, the evaluation decision tree was constructed. The decision tree modeling of evaluation of RLMM construction was gained by the post-pruning approach. The experimental results and analysis show that this model has high precision and credibility.

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

Diagnostics of Track Infrastructure as Part of the Digitisation of Russian Railways

2020 ◽  
Vol 64 (188) ◽  
pp. 149-160
Author(s):  
Janusz Poliński
Keyword(s):  
Diagnostic Tools ◽  
Gradual Transition ◽  
Technical Diagnostics ◽  
Strategic Development ◽  
Railway Infrastructure ◽  
Monitoring And Forecasting ◽  
Infrastructure Maintenance ◽  
Result Analysis ◽  
Railway Maintenance ◽  
Condition Diagnosis

Technical diagnostics is an integral part of the railway maintenance process. Through timely maintenance, in addition to ensuring the safety, functional and technical reliability of the infrastructure, maintenance costs are reduced and downtime losses, due to failures or premature repair requests, are eliminated or reduced. The track infrastructure diagnostic tools have evolved. This is related to, among others, the miniaturisation of instruments, reading accuracy during motion, as well as upgraded measurement automation and result analysis. Currently, data obtained from multifunctional diagnostic tools is the basis for the developed Russian railway infrastructure maintenance and operation digital model. The strategic development of mobile diagnostic labs is the gradual transition to solutions with advanced digital analysis, supported by artificial intelligence, monitoring and forecasting. The article presents the development of mobile labs for the railroad infrastructure condition diagnosis up to the current solutions, in which measurements take place without human intervention and the obtained information is transmitted in real time to the analysis and decision centres. Keywords: rail transport, measuring wagons, digitisation of railways, Russian railways

The application of AI in the aesthetic cultivation of Chinese education

2021 ◽  
pp. 1-5
Author(s):  
Yajuan Wang ◽  
Wen li ◽  
Ruifang Xu
Keyword(s):  
New Media ◽  
Decision Tree ◽  
Chinese Language ◽  
Chinese Students ◽  
Chinese Education ◽  
Coordinated Development ◽  
Language And Literature ◽  
C4.5 Algorithm ◽  
Literature Education ◽  
The Aesthetic

This article will briefly analyse the research background and research significance of the infiltration of aesthetic cultivation in Chinese language and literature education in the context of new media. And through the calculation based on decision tree and C4.5 algorithm, the paper tries to makes the construction of infiltration system of aesthetic cultivation in Chinese language and literature education in the context of new media more scientific and reasonable. This paper also analyses the main connotation and significance of aesthetic cultivation and puts forward the effective infiltration way of aesthetic cultivation in Chinese language and literature in the context of new media, aiming at promoting the comprehensive and coordinated development of Chinese students.

Research on Asset Recognition Algorithm of Information Security Product Based on Decision Tree Algorithm

2013 ◽  
Vol 397-400 ◽  
pp. 2296-2300 ◽  
Author(s):  
Fei Shuai ◽  
Jun Quan Li
Keyword(s):  
Computational Complexity ◽  
Information Security ◽  
Decision Tree ◽  
Recognition Algorithm ◽  
Space Complexity ◽  
Complex Relationship ◽  
Decision Tree Algorithm ◽  
Tree Algorithm ◽  
C4.5 Algorithm ◽  
C4.5 Decision Tree

In current, there are complex relationship between the assets of information security product. According to this characteristic, we propose a new asset recognition algorithm (ART) on the improvement of the C4.5 decision tree algorithm, and analyze the computational complexity and space complexity of the proposed algorithm. Finally, we demonstrate that our algorithm is more precise than C4.5 algorithm in asset recognition by an application example whose result verifies the availability of our algorithm.Keywordsdecision tree, information security product, asset recognition, C4.5

Decision Tree Modeling Using Integrated Multilevel Stochastic Networks

2006 ◽  
Vol 132 (12) ◽  
pp. 1254-1266 ◽  
Author(s):  
Mohamed Moussa ◽  
Janaka Ruwanpura ◽  
George Jergeas
Keyword(s):  
Decision Tree ◽  
Stochastic Networks ◽  
Tree Modeling

scholarly journals DECISION TREE C4.5 ALGORITHM FOR TUITION AID GRANT PROGRAM CLASSIFICATION (CASE STUDY: DEPARTMENT OF INFORMATION SYSTEM, UNIVERSITAS TEKNOKRAT INDONESIA)

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heni Sulistiani ◽  
Ahmad Ari Aldino
Keyword(s):  
Decision Tree ◽  
Classification Model ◽  
Grant Program ◽  
C4.5 Algorithm ◽  
Long Time ◽  
The Right ◽  
Short Time ◽  
Tuition Fee

In pandemic era, almost everyone struggles for their life. College students are such example. They have difficulty in paying tuition fee to continue their study. Based on this problematic situation, Universitas Teknokrat Indonesia grants the students who have good academic performance with tuition fee aid program. Many variables used for determining the grant made it hard to make a decision in a short time or even takes very long time. To make it easier for management to decide who is the right student to get grant, it needs classification model. The purpose of this study is the classification of grant recipients by using decision tree C4.5 algorithm. That can determine whether a potential student can be accepted as an awardee or not. Then, the results of the classification are validated with ten-fold cross validation with an accuracy, precision and recall with the score of 87 % for all part. It means the model perform quite well to be implemented into system.

scholarly journals A Detection algorithm based on Convolutional Neural Network

2018 ◽  
Author(s):  
Fei Rong ◽  
Li Shasha ◽  
Xu Qingzheng ◽  
Liu Kun
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Training Model ◽  
Test Sample ◽  
Training Sample ◽  
Detection Algorithm ◽  
Small Scale ◽  
Detection Model ◽  
Sample Data ◽  
Ratio Change

The Station logo is a way for a TV station to claim copyright, which can realize the analysis and understanding of the video by the identification of the station logo, so as to ensure that the broadcasted TV signal will not be illegally interfered. In this paper, we design a station logo detection method based on Convolutional Neural Network by the characteristics of the station, such as small scale-to-height ratio change and relatively fixed position. Firstly, in order to realize the preprocessing and feature extraction of the station data, the video samples are collected, filtered, framed, labeled and processed. Then, the training sample data and the test sample data are divided proportionally to train the station detection model. Finally, the sample is tested to evaluate the effect of the training model in practice. The simulation experiments prove its validity.

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