We appreciate the comments made by Dr. Sabour about our manuscript. We agree that the term ‘prediction’ can be misleading. We used the term as a general one, since our study employed an explanatory rather than a predictive model.1 We estimated which factors were associated with an unfavorable outcome (defined as a Glasgow outcome scale ≤4) rather than predicting the prognosis of individual pati...

In this work, the time series modeling was used to predict the Tazareh coal mine risks. For this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. Next, a monthly time series diagram related to each one of these indices was for a nine year period of time from 2005 to 2013. After extrusion of the trend, seasonali...

Accident prediction models (APMs) are very useful tools for estimating the expected number of accidents on entities such as intersections and road sections. These estimates are typically used in the identification of sites for possible safety treatment and in the evaluation of such treatments. An APM is, in essence, a mathematical equation that expresses the average accident frequency of a site...

Abstract Millions of people die in road accidents yearly, causing significant damage to the economy and humanity. The main focus study is analyze through Black Spot Identification establish a Prediction Model on Cebu South Coastal Road (CSCR)-N840 Highway. data gathered from government agencies were digitized using SPSS MS Excel. revealed that year 2018 has highest number accident cases with 55...

Millions of people are dying, and billions properties damaged by road traffic accidents each year worldwide. In the case our country Ethiopia, effect is even more causing injuries, death, property damage. Forecasting accident predicting severity contributes a role indirectly in reducing accidents. This study deals with forecasting number prediction an Oromia Special Zone using deep artificial n...

abstract accurate prediction of hourly minimum temperature is required for various crop models which simulate photosynthesis and transpiration. such data can be used for crop protection and reducing the crops injuries due to freezing as well. our objective of this study is employing trigonometric and pattern recognition (k-nn) approaches to evaluate their potential in prediction of hourly tempe...

This study describes the experimental application of Machine Learning techniques to build prediction models that can assess the injury risk associated with traffic accidents. This work uses an freely available data set of traffic accident records that took place in the city of Porto Alegre/RS (Brazil) during the year of 2013. This study also provides an analysis of the most important attributes...

The quality-control method is improved and used to identify accident black spots on highway. A neural networks prediction model based on three layers BP network is suggested to predict road traffic accident. The dynamic accident power method for macroscopic evaluation is put forward and the concept of highway accident coefficient is advanced in the method. With large numbers of actual traffic a...