Algorithms for clustering data
Algorithms for clustering data
Introduction to neural networks
Introduction to neural networks
The nature of statistical learning theory
The nature of statistical learning theory
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Information Theoretic Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Machine Learning
Fuzzy and Neural Approaches in Engineering
Fuzzy and Neural Approaches in Engineering
Machine Learning
A decision support system based on support vector machines for diagnosis of the heart valve diseases
Computers in Biology and Medicine
Breast cancer diagnosis using least square support vector machine
Digital Signal Processing
Expert Systems with Applications: An International Journal
Comparison of clustering algorithms for analog modulation classification
Expert Systems with Applications: An International Journal
A decision making system to automatic recognize of traffic accidents on the basis of a GIS platform
Expert Systems with Applications: An International Journal
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Self-learning fuzzy controllers based on temporal backpropagation
IEEE Transactions on Neural Networks
Automatic determination of traffic accidents based on KMC-based attribute weighting
Neural Computing and Applications - Special Issue on LSMS2010 and ICSEE 2010
| Hi-index | 0.00 |
A case study including the discrimination of traffic accidents as accident free and accident cases on Konya-Afyonkarahisar highway in Turkey using the proposed hybrid method based on combining of a new data preprocessing method called subtractive clustering attribute weighting (SCAW) and classifier algorithms with the help of Geographical Information System (GIS) technology has been conducted. In order to improve the discrimination of classifier algorithms including artificial neural network (ANN), adaptive network based fuzzy inference system (ANFIS), support vector machine, and decision tree, using data preprocessing need in solution of these kinds of problems (traffic accident case study). So, we have proposed a novel data preprocessing method called subtractive clustering attribute weighting (SCAW) and combined with classifier algorithms. In this study, the experimental data has been obtained by means of using GIS. The obtained GIS attributes are day, temperature, humidity, weather conditions, and month of occurred accident. To evaluate the performance of the proposed hybrid method, the classification accuracy, sensitivity and specificity values have been used. The experimental obtained results are 53.93%, 52.25%, and 38.76% classification successes using alone ANN, ANFIS, and SVM with RBF kernel type, respectively. As for the proposed hybrid method, the classification accuracies of 67.98%, 70.22%, and 61.24% have been obtained using the combination of SCAW with ANN, the combination of SCAW with SVM (radial basis function (RBF) kernel type), and the combination of SCAW with ANFIS, respectively. The proposed SCAW method with the combination of classifier algorithms has been achieved the very promising results in the discrimination of traffic accidents.