Accident Analysis by Using Data Mining Techniques

Prayag Tiwari

ISBN 10: 3668613087 / ISBN 13: 9783668613089

Published by GRIN Verlag, 2018

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2017 in the subject Computer Sciences - Industry 4.0, grade: 5.0/5.0, , course: Computer Science and Engineering, language: English, abstract: Accident data analysis is one of the prime interests in the present era. Analysis of accident is very essential because it can expose the relationship between the different types of attributes that commit to an accident. Road, traffic and airplane accident data have different nature in comparison to other real world data as accidents are uncertain. Analyzing diverse accident dataset can provide the information about the contribution of these attributes which can be utilized to deteriorate the accident rate. Nowadays, Data mining is a popular technique for examining the accident dataset. In this study, Association rule mining, different classification, and clustering techniques have been implemented on the dataset of the road, traffic accidents, and an airplane crash. Achieved result illustrated accuracy at a better level and found many different hidden circumstances that would be helpful to deteriorate accident ratio in near future.

Seller Inventory # 9783668613089

Bibliographic Details

• Title: Accident Analysis by Using Data Mining Techniques
• Publisher: GRIN Verlag
• Publication Date: 2018
• Language: English
• ISBN 10: 3668613087
• ISBN 13: 9783668613089
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 7D millimeters 210 millimeters width by 148 millimeters height by 7 millimeters depth
• Weight: 135 grams

About this title

Synopsis

Master's Thesis from the year 2017 in the subject Computer Sciences - Industry 4.0, grade: 5.0/5.0, course: Computer Science and Engineering, language: English, abstract: Accident data analysis is one of the prime interests in the present era. Analysis of accident is very essential because it can expose the relationship between the different types of attributes that commit to an accident. Road, traffic and airplane accident data have different nature in comparison to other real world data as accidents are uncertain. Analyzing diverse accident dataset can provide the information about the contribution of these attributes which can be utilized to deteriorate the accident rate. Nowadays, Data mining is a popular technique for examining the accident dataset. In this study, Association rule mining, different classification, and clustering techniques have been implemented on the dataset of the road, traffic accidents, and an airplane crash. Achieved result illustrated accuracy at a better level and found many different hidden circumstances that would be helpful to deteriorate accident ratio in near future.

About the Author

Prayag Tiwari is working as a Research Fellow at University of Padova, Italy. His research areas focus on Machine Learning, Deep Learning, IoT, Image Processing, Data Warehousing etc. He received his MS from NUST MISIS, Moscow. He worked also as a Research Assistant in NUST MISIS as well he has Teaching and Industrial work experience. He has several publications in Journal, Book Series and Conferences of IEEE, Springer, Elsevier, Wiley, IGI-Global etc..