Highway traffic accident prediction using VDS big data analysis
S Park, S Kim, Y Ha - The Journal of Supercomputing, 2016 - Springer
In modern society, accidents on the roads are one of the most life-threatening dangers to
humans. Traffic accidents that cause a lot of damages are occurring all over the places. The …
humans. Traffic accidents that cause a lot of damages are occurring all over the places. The …
[PDF][PDF] Machine learning methods of kernel logistic regression and classification and regression trees for landslide susceptibility assessment at part of Himalayan area …
BT Pham, I Prakash - Indian J. Sci. Technol, 2018 - researchgate.net
1Department of Geotechnical Engineering, University of Transport Technology, 54 Trieu
Khuc, Thanh Xuan, Ha Noi, Viet Nam; binhpt@ utt. edu. vn 2Department of Science & …
Khuc, Thanh Xuan, Ha Noi, Viet Nam; binhpt@ utt. edu. vn 2Department of Science & …
Classification of simultaneous multiple partial discharge sources based on probabilistic interpretation using a two-step logistic regression algorithm
In online condition assessment monitoring of high voltage (HV) insulators, it is often required
to identify multiple, simultaneously activated partial discharge (PD) sources that happen in …
to identify multiple, simultaneously activated partial discharge (PD) sources that happen in …
Large imbalance data classification based on mapreduce for traffic accident prediction
SH Park, YG Ha - … conference on innovative mobile and internet …, 2014 - ieeexplore.ieee.org
In modern society, our everyday life has a close connection with traffic issues. One of the
most burning issues is about predicting traffic accidents. Predicting accidents on the road …
most burning issues is about predicting traffic accidents. Predicting accidents on the road …
Motor imagery EEG signal classification on DWT and crosscorrelated signal features
Motor imagery (MI) based electroencephalogram (EEG) signals are a widely used form of
input in brain computer interface systems (BCIs). Although there are a number of ways to …
input in brain computer interface systems (BCIs). Although there are a number of ways to …
Bankruptcy prediction using data mining techniques
M Wagle, Z Yang, Y Benslimane - 2017 8th International …, 2017 - ieeexplore.ieee.org
This paper discusses the application and benefits of data mining techniques to construct
prediction models in the field of corporate bankruptcy. It analyzes a dataset of 120 …
prediction models in the field of corporate bankruptcy. It analyzes a dataset of 120 …
Faulty sensor data detection in wireless sensor networks using logistical regression
T Zhang, Q Zhao, Y Nakamoto - 2017 IEEE 37th International …, 2017 - ieeexplore.ieee.org
Wireless sensor networks (WSNs) are commonly used to monitor changes in an
environment and prevent disasters such as structural instability, forest fires, and tsunami …
environment and prevent disasters such as structural instability, forest fires, and tsunami …
Design and evaluation of logistic regression model for pattern recognition systems
P Rao, J Manikandan - 2016 IEEE Annual India Conference …, 2016 - ieeexplore.ieee.org
In this paper, an attempt is made to design pattern recognition systems using logistic
regression model and few mapping functions are proposed for the same. The performance …
regression model and few mapping functions are proposed for the same. The performance …
Partial discharge source classification using pattern recognition algorithms
H Janani - 2016 - mspace.lib.umanitoba.ca
Abstract Design, development, and testing of a comprehensive and automated classification
system for single and multiple PD source identification based on the relationship between …
system for single and multiple PD source identification based on the relationship between …
A mobile device prototype application for the detection and prediction of node faults in wireless sensor networks
Various implementations of wireless sensor networks (ie personal area-, wireless body area-
networks) are prone to node and network failures by such characteristics as limited node …
networks) are prone to node and network failures by such characteristics as limited node …