Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction
نویسندگان
چکیده
We are developing dynamic relational knowledge discovery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thunderstorms, hail, and floods, annually cause significant loss of life, property destruction, and disruption of the transportation systems. The annual economic impact of these mesoscale storms is estimated to be greater than $13B (Pielke and Carbone, 2002). Any mitigation of the effects of these storms would be beneficial. However, current techniques for predicting severe weather are tied to specific characteristics of the radar systems. Each new sensing system requires the development of new radar detection algorithms for detecting hazardous events. Our research focuses on developing new dynamic relational models that will enable meteorologists to improve their understanding of the formation of tornados and other severe weather events.
منابع مشابه
Application of Chaos Theory in Hazardous Material Transportation
Risk factors are generally defined and assigned to road networks, as constant measures in hazmat routing problems. In fact, they may be dynamic variables depending on traffic volume, weather and road condition, and drivers' behavior. In this research work, risk factors are defined as dynamic variables using the concept of chaos theory. The largest Lyapunov exponent is utilized to determine the ...
متن کاملAdvances in Operational Weather Radar Technology
n The U.S. aviation system makes extensive use of national operational Doppler weather radar networks. These are critical for the detection and forecasting of thunderstorms and other hazardous weather phenomena, and they provide dense, continuously updated measurements of precipitation and wind fields as inputs to high-resolution numerical weather prediction models. This article describes recen...
متن کاملCalibration of Traffic Flow Models under Adverse Weather and Application in Mesoscopic Network Simulation Procedures
1 2 ABSTRACT 3 4 The weather-sensitive Traffic Estimation and Prediction System (TrEPS) aims to accurately 5 estimate and predict traffic state under inclement weather conditions. Successful application 6 of weather-sensitive TrEPS requires detailed calibration of weather effects on traffic flow 7 model. In this paper, systematic procedures of the entire calibration process are developed, 8 fro...
متن کاملInitialization of Tropical Cyclone Structure for Operational Application
The long-term goal of this project is to improve the prediction of tropical cyclone (TC) genesis, structure and intensity changes through improved representation of 3-dimensional TC structure at the initial time. The accurate prediction of TC genesis, structure and intensity changes is critical to Navy missions and civilian activities in coastal areas. Significant gains have been made in the TC...
متن کاملDetermination of Financial Failure Indicators by Gray Relational Analysis and Application of Data Envelopment Analysis and Logistic Regression Analysis in BIST 100 Index
Financial failure prediction models have been developed by using Logistic Regression (LR) analysis from traditional statistical methods and Data Envelopment Analysis (DEA), which is a mathematically based nonparametric method over the financial reports of the companies traded in The Istanbul Stock Exchange National 100 Index (BIST 100) between the years 2014-2016. In the development of these mo...
متن کامل