Traffic Accident Severity Prediction Based on Decision Level Fusion of Machine and Deep Learning скачать в хорошем качестве

Traffic Accident Severity Prediction Based on Decision Level Fusion of Machine and Deep Learning

TO PURCHASE OUR PROJECTS IN ONLINE (OR) OFFLINE CONTACT:VENKAT PROJECTS NAME: VENKATARAO GANIPISETTY Mobile & WhatsApp :+91 9966499110 Email :[email protected] Website:www.venkatjavaprojects.com About Project: In propose paper author is introducing new machine learning algorithm called RFCNN (Random Forest Convolution Neural Neural) to predict accident severity. In propose algorithm author combining two models called RF and CNN to enhance accident prediction accuracy and then compare its performance with various machine learning algorithms called Random Forest (RF), Ada Boost (AC), Extra Tree Classifier (ETC), Gradient Boosting (GBM), Voting Classifier (VC (LR+SGD)), CNN. In all algorithms propose RFCNN is giving high accuracy, to train all algorithms author using USA Road Accident Dataset which consist of 47 features and author evaluating all algorithms performance using all 47 features (full features) and 23 selected features and for both dataset variants RFCNN is giving better accuracy.