Road Crash Prediction Models: Different Statistical Modeling Approaches

Factors affecting road crash modeling

Single-Vehicle Run-Off-Road Crash Prediction Model Associated with Pavement Characteristics

This study aims to evaluate the impact of pavement physical characteristics on the frequency of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order to achieve this goal and to introduce the most accurate crash prediction model (CPM), authors have tried to develop generalized linear models, including the Poisson regression (PR), negative binomial regression (...

A Framework for Real-time Crash Prediction: Statistical Approach Versus

The attempts to predict crashes on freeways through statistical modeling involving capacity driven measures of traffic flow (e.g., AADT) and road geometry have spanned for more than two decades. However, success in crash prediction involving these static data has so far been limited. In recent times, some researchers made efforts to accommodate the weather conditions and seasonal effects to bet...

Statistical Approaches to Predictive Modeling

Prediction, i.e., predicting the potential values or value distributions of certain attributes for objects in a database or data warehouse, is an attractive goal in data mining. To predict future events not shown in databases with high quality can help users to make smart business decisions. With the concern of both scalability and high quality of prediction, we propose a predictive modeling al...

Evaluating Different Approaches to Permeability Prediction in a Carbonate Reservoir

Permeability can be directly measured using cores taken from the reservoir in the laboratory. Due to high cost associated with coring, cores are available in a limited number of wells in a field. Many empirical models, statistical methods, and intelligent techniques were suggested to predict permeability in un-cored wells from easy-to-obtain and frequent data such as wireline logs. The main obj...