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Accident Analysis & Prevention
Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are preferred for their ability to estimate effect sizes using variable coefficients and elasticity effects ...
Diwas Thapa +3 more
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Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are preferred for their ability to estimate effect sizes using variable coefficients and elasticity effects ...
Diwas Thapa +3 more
openaire +2 more sources
Predicting and Preventing Fatal Crashes
2019 Twelfth International Conference on Contemporary Computing (IC3), 2019A conservative estimate of crash reports of highways would suggest that more than 90% crashes could be attributed to human errors, rest factors are either environmental or are uncertain. Collisions especially at the intersections have hit it off to an alarming rate and hence there is a dire need for a medium that helps preventing fatal crashes.
Kavita Pandey +4 more
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A crash-prediction model for road tunnels
Accident Analysis & Prevention, 2013Considerable research has been carried out into open roads to establish relationships between crashes and traffic flow, geometry of infrastructure and environmental factors, whereas crash-prediction models for road tunnels, have rarely been investigated.
CALIENDO, Ciro +2 more
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Accident Analysis & Prevention, 1979
Automobile crash injury was analyzed using data from the Crash Performance Injury Report (CPIR) for crashes which occurred since 1 January 1970 involving 1969 or newer cars, vans and pickup trucks. An injury prediction model was developed using delta V, vehicle weight, occupant age, seating position, crash configuration, and restraint usage to predict ...
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Automobile crash injury was analyzed using data from the Crash Performance Injury Report (CPIR) for crashes which occurred since 1 January 1970 involving 1969 or newer cars, vans and pickup trucks. An injury prediction model was developed using delta V, vehicle weight, occupant age, seating position, crash configuration, and restraint usage to predict ...
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Rollover crashes: Predicting serious injury based on occupant, vehicle, and crash characteristics
Accident Analysis & Prevention, 2006The purpose of this research was to determine occupant, vehicle, and crash characteristics predicting serious injury during rollover crashes. We compared 27 case occupants with serious or greater severity injuries with 606 control occupants without injury or with only minor or moderate injury.
Carol, Conroy +9 more
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Linear regression crash prediction models
2008Virginia.
Rakha, Hesham A. +4 more
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Predicting Offenses and Crashes from Young Drivers' Offense and Crash Histories
Journal of Crash Prevention and Injury Control, 2001Previous research has indicated that offenses are better predictors of subsequent crashes than crashes themselves. We examined this hypothesis for 13,800 young beginning drivers in Michigan for up to nine years during the initial years of driving. Our analyses indicated that previous-year offenses are better predictors of both subsequent-year offenses ...
MICHAEL R. ELLIOTT +3 more
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High-Frequency Runs and Flash Crash Predictability
SSRN Electronic Journal, 2014This article describes research into the short-term nature of movements in price data. The study’s key finding is that asset returns do not evolve at the Gaussian increments commonly assumed by continuous pricing models. Instead, prices exhibit strong autocorrelation, often resulting in predictable one-directional sequences, or runs.
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Predicting Stock Market Crashes in China
The Journal of Portfolio Management, 2018Predicting stock market crashes is extremely valuable for all investors. Several useful prediction models have been developed, focusing on mature financial markets, in North America, Europe, and Japan. The authors investigate whether traditional crash predictors—the price-to-earnings ratio (P/E), the cyclically adjusted price-to-earnings ratio (CAPE ...
Sébastien Lleo, William T. Ziemba
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Predicting method crashes with bytecode operations
Proceedings of the 6th India Software Engineering Conference, 2013Software monitoring systems have high performance overhead because they typically monitor all processes of the running program. For example, to capture and replay crashes, most current systems monitor all methods; thus yielding a significant performance overhead. Lowering the number of methods being monitored to a smaller subset can dramatically reduce
Sunghun Kim +4 more
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