Results 31 to 40 of about 99,827 (273)
Application of hybrid support vector Machine models in analysis of work zone crash injury severity
Transportation Research Interdisciplinary Perspectives, 2023 Crash severity models are often used to analyze the adverse effects of highway work zones on traffic safety. In this study we evaluated application of hybrid support vector machine (SVM) and hyperparameter optimization models for improved accuracy of ...
Branislav Dimitrijevic +2 more
doaj +1 more source
Diagnosis and Prediction of Market Rebounds in Financial Markets [PDF]
, 2010 We introduce the concept of "negative bubbles" as the mirror image of standard financial bubbles, in which positive feedback mechanisms may lead to transient accelerating price falls. To model these negative bubbles, we adapt the Johansen-Ledoit-Sornette
Sornette, Didier +2 more
core +1 more source
Housing Market Crash Prediction Using Machine Learning and Historical Data [PDF]
, 2020 The 2008 housing crisis was caused by faulty banking policies and the use of credit derivatives of mortgages for investment purposes. In this project, we look into datasets that are the markers to a typical housing crisis.
De, Parnika
core +1 more source
Logistic model for stock market bubbles and anti-bubbles [PDF]
, 2017 Log-periodic power laws often occur as signatures of impending criticality of hierarchical systems in the physical sciences. It has been proposed that similar signatures may be apparent in the price evolution of financial markets as bubbles and the ...
Lynch, Christopher, Mestel, Benjamin
core +1 more source
Predicting financial crashes using discrete scale invariance [PDF]
The Journal of Risk, 1999 We present a synthesis of all the available empirical evidence in the light of recent theoretical developments for the existence of characteristic log-periodic signatures of growing bubbles in a variety of markets including 8 unrelated crashes from 1929 to 1998 on stock markets as diverse as the US, Hong-Kong or the Russian market and on currencies. To
Johansen, Anders +2 more
openaire +2 more sources
IEEE Access, 2018 Crash injury severity prediction is a promising research target in traffic safety. Traditionally, various statistical methods were used for modeling crash injury severities. In recent years, machine learningbased methods are becoming popular due to their
Jian Zhang +3 more
doaj +1 more source
Crash severity analysis: A data-enhanced double layer stacking model using semantic understanding
HeliyonThe crash severity analysis is of significant importance in traffic crash prevention and emergency resource allocation. A range of innovations offers potential traffic crash severity prediction models to improve road safety.
Di Yang, Tao Dong, Peng Wang
doaj +1 more source
Scientific Reports, 2022 Road traffic injuries are one of the primary reasons for death, especially in developing countries like Bangladesh. Safety in land transport is one of the major concerns for road safety authorities and other policymakers.
Hanif Bhuiyan +8 more
doaj +1 more source
Do Elevated Gravitational-Force Events While Driving Predict Crashes and Near Crashes? [PDF]
American Journal of Epidemiology, 2012 The purpose of this research was to determine the extent to which elevated gravitational-force event rates predict crashes and near crashes. Accelerometers, global positioning systems, cameras, and other technology were installed in vehicles driven by 42 newly licensed Virginia teenage drivers for a period of 18 months between 2006 and 2009.
Bruce G, Simons-Morton +3 more
openaire +2 more sources
Testing for financial crashes using the Log Periodic Power Law mode [PDF]
, 2013 A number of papers claim that a Log Periodic Power Law (LPPL) fitted to financial market bubbles that precede large market falls or 'crashes', contain parameters that are confined within certain ranges.
Bree, David S., Joseph, Nathan Lael
core +2 more sources