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Investigating adoption patterns of residential low impact development (LID) using classification trees

Environment Systems and Decisions 2019年第3期39卷 295-306页

作者： Amodeo, Domenico c. Francis, Royce A. Department of Engineering Management and Systems Engineering The George Washington University Washington 20052 DC United States

Local governments are under pressure to improve storm water management and often times must comply with consent decrees with the Federal Government. Decentralizing a portion of the storm water management by integrating private landowners into localized retention and infiltration efforts, that is, low impact development (LID) or green infrastructure projects, is becoming increasingly popular. Some wastewater systems have considered incentivizing private land owners to make improvements aimed at retaining storm water or slowing the conveyance to grey infrastructure. This study examines potential opportunities for incentivizing private residential land owners in Washington Dc to install LID projects. This study maps LID configurations to a set of adoption strategies and categories. The c4.5 algorithm is then applied to identify a high performance decision tree for classifying parcels by adoption strategy or adoption categories based on property-level attributes. © 2019, Springer Science+Business Media, LLc, part of Springer Nature.

关键词： Adopters, green city Best management practices c4.5 algorithm combined sewage overflow cSO Decision trees Environmental policy Green roofs Impervious Infiltration Landscaping LID Low impact development Machine learning Permeable Rain barrels Run-off Storm water management Storm water retention Urban planning Water quality

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Application of Data Mining for Decision Tree Model of Multi-variety Discrete Production and Manufacture

Application of Data Mining for Decision Tree Model of Multi-...

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3rd International Symposium on Intelligent Information Technology and Security Informatics

作者： Sun, Jianfang South China Univ Technol Sch Mech & Automot Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780769540207

In this paper, taking the decision attributes, including order number, product number, manhour and comprehensive evaluation into account, the decision tree model of discrete production and manufacture has been presented. And c4.5 algorithm has been used to construct the decision tree recursively in a topdown manner, in which the topmost node is the root node, each internal node denotes an attribute test, each branch represents an outcome of the test, and each leaf node represents classes. Then RFc (Remote Function call) has been used to extract data from SAP (Systems Applications and Products in Data Processing) R/3 system to decision-making database, and DTS (Data Transformation Service) used to extract data from MES (Manufacturing Execution System) to decision-making database, which can supply useful data resource for data mining. Finally, a case study has been analyzed to show the application of the decision tree model. The decision tree has been implied to be references to the real discrete production and manufacture.

关键词： data mining discrete production and manufacture decision tree c4.5 algorithm

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Online Dissolved Gas Analysis of Power Transformers Based on Decision Tree Model 4

Online Dissolved Gas Analysis of Power Transformers Based on...

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4th IEEE conference on Power Engineering and Renewable Energy (IcPERE)

作者： Basuki, Arief Suwarno Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9781538674567

This paper presents the possibility of using one of machine learning model, decision tree with c4.5 algorithm for gas interpretation in online condition monitoring and diagnostic application of power transformers. Decision tree selection is based on the best learning outcomes of machine learning software (WEKA and Orange) compared to naive Bayes, neural network, nearest neighbour and support vector machine models. The decision tree was built from 715 data, 7 attributes of gas and 9 types of fault which were cleaned by interquartile range method become 471 data. Evaluation result based on correction prediction are 95.54% using data training, 88.32% using cross validation and 87.23% using 10% random data from data training. The decision tree rule was implemented in online condition monitoring and diagnostic of power transformer which is integrated into ScADA system. This implementation result can predict transformers fault from gas values by online better than conventional DGA methods.

关键词： Dissolved Gas Analysis Decision Tree Machine Learning c4.5 algorithm ScADA

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Decision Trees on the Foreign Exchange Market 8th

Decision Trees on the Foreign Exchange Market

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8th KES International conference on Intelligent Decision Technologies (KES-IDT)

作者： Przemyslaw, Juszczuk Jan, Kozak Katarzyna, Trynda Univ Silesia Inst Comp Sci Sosnowiec Poland Univ Econom Fac Informat & Commun Chair Knowledge Engn Katowice Poland

ISBN: (纸本)9783319396279;9783319396262

In this article we present a novel approach to generate a data set directly from real-world forex market data. The data are transformed into a decision table. Every single object in such a table consists of conditional attributes-in this case values of technical analysis indicators as well as of the decision class (BUY, SELL or WAIT). Our second goal was to test the quality of the classification based on two well-known algorithms used for decision tree construction: the cART algorithm and the c4.5 algorithm. All experiments were conducted on three different currency pairs-with 3 data sets for each pair.

关键词： Forex market Decision tree cART c4.5 algorithm

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Diagnosis of coronary Artery Disease Using cost-Sensitive algorithms

Diagnosis of Coronary Artery Disease Using Cost-Sensitive Al...

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12th IEEE International conference on Data Mining (IcDM)

作者： Alizadehsani, Roohallah Hosseini, Mohammad Javad Sani, Zahra Alizadeh Ghandeharioun, Asma Boghrati, Reihane Sharif Univ Technol Dept Comp Engn Tehran Iran

ISBN: (纸本)9780769549255;9781467351645

One of the main causes of death the world over are cardiovascular diseases, of which coronary artery disease (cAD) is a major type. This disease occurs when the diameter narrowing of one of the left anterior descending, left circumflex, or right coronary arteries is equal to or greater than 50 percent. Angiography is the principal diagnostic modality for the stenosis of heart vessels;however, because of its complications and costs, researchers are looking for alternative methods such as data mining. This study conducts data mining algorithms on the Z-Alizadeh Sani dataset which has been collected from 303 random visitors to Tehran's Shaheed Rajaei cardiovascular, Medical and Research center. In this paper, the reason of effectiveness of a preprocessing algorithm on the dataset is investigated. This algorithm which has been merely introduced in our previous works, extracts three new features from the dataset. These features are then used to enrich the primary dataset in order to achieve more accurate results. Moreover, despite the fact that misclassification of diseased patients has more side effects than that of healthy ones, to the best of our knowledge cost-sensitive algorithms have yet to be used in this field. Therefore, in this paper 10-fold cross validation on cost-sensitive algorithms along with base classifiers of Naive Bayes, Sequential Minimal Optimization (SMO), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and c4.5 were employed. As a result, the SMO algorithm has yield to very high sensitivity (97.22%) and accuracy (92.09%) rates, the likes of which have not been reported simultaneously in the existing literature.

关键词： component Naive Bayes algorithm Data Mining coronary Artery Disease c4.5 algorithm cost Sensitive algorithms Feature Extraction

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A Smart Bus Tracking System Based on Location-Aware Services and QR codes

A Smart Bus Tracking System Based on Location-Aware Services...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Eken, Suleyman Sayar, Ahmet Kocaeli Univ Dept Comp Engn Kocaeli Turkey

ISBN: (纸本)9781479930203

When it comes to taking the public transportation, time and patience are of essence. In other words, many people using public transport buses have experienced time loss because of waiting at the bus stops. In this paper, we proposed smart bus tracking system that any passenger with a smart phone or mobile device with the QR (Quick Response) code reader can scan QR codes placed at bus stops to view estimated bus arrival times, buses' current locations, and bus routes on a map. Anyone can access these maps and have the option to sign up to receive free alerts about expected bus arrival times for the interested buses and related routes via SMS and e-mails. We used c4.5 (a statistical classifier) algorithm for the estimation of bus arrival times to minimize the passengers waiting time. GPS (Global Positioning System) and Google Maps are used for navigation and display services, respectively.

关键词： QR codes GPS Smart bus stops c4.5 algorithm Smart phones Interactive maps

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The application of decision tree algorithm in intelligent circuit breaker 2

The application of decision tree algorithm in intelligent ci...

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2nd International conference on Reliability of Electrical Products and Electrical contacts

作者： Wang, Zhenzhou Wang, Jinying Liu, Jiaomin N China Elect Power Univ Coll Elect Engn Baoding 071003 Peoples R China

ISBN: (纸本)9787504646293

Decision Tree algorithm was applied in intelligent circuit breaker based on analying the switch tactic and deficiency of traditional circuit breaker. In the process, c4.5 extracted knowledge automatically from the information collected by circuit breaker, builded up decision tree based on the maximum information gain modulus and according to the acquired knoledge, then carrid on a simplification. The intelligent circuit breaker that adopts the decision tree calculate algorithm has the higher power supply credibility and safety.

关键词： circuit breaker decision tree c4.5 algorithm

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Intelligent Placement Model Based On Decision Tree 9

Intelligent Placement Model Based On Decision Tree

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9th International conference on Information Technology in Medicine and Education (ITME)

作者： cai, congYu Lu, Huijuan Yan, Ke Ye, Minchao China Jiliang Univ Coll Informat Engn Hangzhou 310018 Zhejiang Peoples R China

ISBN: (纸本)9781538677438

Recently, the analysis of big data based on artificial intelligence algorithms has shown great potential in the field of education system However, due to the complexity of the education system, the problem of students' placement in primary and secondary schools (matching problem of students and teachers) still exists. This paper proposes a placement model using ID3 and c4.5 bagging algorithms. The proposed model uses the characteristics and academic performances of students to train the decision tree and performs appropriate pruning to implement the decision trees. In the experimental results, the proposed method (ID3 algorithms and c4.5 algorithm) achieves high matching accuracy.

关键词： Decision tree placement model c4.5 algorithm ID3 algorithm bagging

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comparison of classification Techniques for predicting the cognitive Skill of Students in Education Environment 5

Comparison of Classification Techniques for predicting the C...

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5th IEEE International conference on computational Intelligence and computing Research (IEEE IccIc)

作者： Mayilvaganan, M. Kalpanadevi, D. PSG Coll Arts & Sci Coll Dept Comp Sci Coimbatore Tamil Nadu India

ISBN: (纸本)9781479939756

The proposed methodology involves to compares classification techniques for predicting the cognitive skill of students which can be evaluate by conducting the online test. The paper focuses the comparative performance of c4.5 algorithm, Naive Bayes classifier algorithm which one is well suited accuracy for predicting the skill of expertise by experimenting in Rapid miner.

关键词： Datamining c4.5 algorithm Naive Bayes classification Rapid Miner

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Identification of Encryption algorithm Using Decision Tree

Identification of Encryption Algorithm Using Decision Tree

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1st International conference on computer Science and Information Technology

作者： Manjula, R. Anitha, R. PSG Coll Technol Dept Math & Comp Applicat Coimbatore Tamil Nadu India

ISBN: (纸本)9783642178801

The task of identification of encryption algorithm from cipher text alone is considered to be a challenging one. Very few works have been done in this area by considering block ciphers or symmetric key ciphers. In this paper, we propose an approach for identification of encryption algorithm for various ciphers using the decision tree generated by c4.5 algorithm. A system which extracts eight features from a cipher text and classifies the encryption algorithm using the c4.5 classifier is developed. Success rate of this proposed method is in the range of 70 to 75 percentages.

关键词： ciphers Decision tree c4.5 algorithm

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