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Articles 1 - 14 of 14
Full-Text Articles in Statistical Models
Aircraft Damage Classification By Using Machine Learning Methods, Tüzün Tolga İnan
Aircraft Damage Classification By Using Machine Learning Methods, Tüzün Tolga İnan
International Journal of Aviation, Aeronautics, and Aerospace
Safety is the most significant factor that affected incidents (non-fatal) and accidents (fatal) in civil aviation history related to scheduled flights. In the history of scheduled flights, the total incident and accident number until 2022 is 1988. In this study, 677 of them are taken into consideration since 11 September 2001. The purpose of this study is to reveal the factors that can classify type of aircraft damages such as none, minor and substantial in all-time incidents and accidents. ML algorithms with different configurations are applied for the classification process. The RFE and PCA are used to find the most …
Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal
Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal
International Journal of Aviation, Aeronautics, and Aerospace
Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.
We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …
Statistical Characteristics Of High-Frequency Gravity Waves Observed By An Airglow Imager At Andes Lidar Observatory, Alan Z. Liu, Bing Cao
Statistical Characteristics Of High-Frequency Gravity Waves Observed By An Airglow Imager At Andes Lidar Observatory, Alan Z. Liu, Bing Cao
Publications
The long-term statistical characteristics of high-frequency quasi-monochromatic gravity waves are presented using multi-year airglow images observed at Andes Lidar Observatory (ALO, 30.3° S, 70.7° W) in northern Chile. The distribution of primary gravity wave parameters including horizontal wavelength, vertical wavelength, intrinsic wave speed, and intrinsic wave period are obtained and are in the ranges of 20–30 km, 15–25 km, 50–100 m s−1, and 5–10 min, respectively. The duration of persistent gravity wave events captured by the imager approximately follows an exponential distribution with an average duration of 7–9 min. The waves tend to propagate against the local background winds and …
Data Mining And Machine Learning To Improve Northern Florida’S Foster Care System, Daniel Oldham, Nathan Foster, Mihhail Berezovski
Data Mining And Machine Learning To Improve Northern Florida’S Foster Care System, Daniel Oldham, Nathan Foster, Mihhail Berezovski
Beyond: Undergraduate Research Journal
The purpose of this research project is to use statistical analysis, data mining, and machine learning techniques to determine identifiable factors in child welfare service records that could lead to a child entering the foster care system multiple times. This would allow us the capability of accurately predicting a case’s outcome based on these factors. We were provided with eight years of data in the form of multiple spreadsheets from Partnership for Strong Families (PSF), a child welfare services organization based in Gainesville, Florida, who is contracted by the Florida Department for Children and Families (DCF). This data contained a …
Application Of A Hybrid Statistical–Dynamical System To Seasonal Prediction Of North American Temperature And Precipitation, Sarah Strazzo, Dan C. Collins, Andrew Schepen, Q. J. Wang, Emily Becker, Liweli Jia
Application Of A Hybrid Statistical–Dynamical System To Seasonal Prediction Of North American Temperature And Precipitation, Sarah Strazzo, Dan C. Collins, Andrew Schepen, Q. J. Wang, Emily Becker, Liweli Jia
Publications
Recent research demonstrates that dynamical models sometimes fail to represent observed teleconnection patterns associated with predictable modes of climate variability. As a result, model forecast skill may be reduced. We address this gap in skill through the application of a Bayesian postprocessing technique—the calibration, bridging, and merging (CBaM) method—which previously has been shown to improve probabilistic seasonal forecast skill over Australia. Calibration models developed from dynamical model reforecasts and observations are employed to statistically correct dynamical model forecasts. Bridging models use dynamical model forecasts of relevant climate modes (e.g., ENSO) as predictors of remote temperature and precipitation. Bridging and calibration …
The Influence Of Model Resolution On The Simulated Sensitivity Of North Atlantic Tropical Cyclone Maximum Intensity To Sea Surface Temperature, Sarah Strazzo, James Elsner, Timothy Larow, Hiroyuki Murakami, Michael Wehner, Ming Zhao
The Influence Of Model Resolution On The Simulated Sensitivity Of North Atlantic Tropical Cyclone Maximum Intensity To Sea Surface Temperature, Sarah Strazzo, James Elsner, Timothy Larow, Hiroyuki Murakami, Michael Wehner, Ming Zhao
Publications
No abstract provided.
Hurricanes And Climate The U.S. Clivar Working Group On Hurricanes, Kevin J.E. Walsh, Suzana J. Camargo, Gabriel A. Vecchi, Anne Sophie Daloz, James Elsner, Kerry Emanuel, Michael Horn, Young-Kwon Lim, Malcom Roberts, Christina Patricola, Enrico Scoccimarro, Adam H. Sobel, Sarah Strazzo, Gabrielle Villarini, Michael Wehner, Ming Zhao, James P. Kossin, Tim Larow, Kazuyoshi Oouchi, Sigfried Schubert, Hui Wang, Julio Bacmeister, Ping Chang, Fabrice Chauvin, Christiane Jablonowski, Arun Kumar, Hiroyuki Murakami, Tomoaki Ose, Kevin A. Reed, Ramalingam Saravanan, Yohei Yamada, Colin M. Zarzycki, Pier Luigi Vidale, Jefferey A. Jonas, Naomi Henderson
Hurricanes And Climate The U.S. Clivar Working Group On Hurricanes, Kevin J.E. Walsh, Suzana J. Camargo, Gabriel A. Vecchi, Anne Sophie Daloz, James Elsner, Kerry Emanuel, Michael Horn, Young-Kwon Lim, Malcom Roberts, Christina Patricola, Enrico Scoccimarro, Adam H. Sobel, Sarah Strazzo, Gabrielle Villarini, Michael Wehner, Ming Zhao, James P. Kossin, Tim Larow, Kazuyoshi Oouchi, Sigfried Schubert, Hui Wang, Julio Bacmeister, Ping Chang, Fabrice Chauvin, Christiane Jablonowski, Arun Kumar, Hiroyuki Murakami, Tomoaki Ose, Kevin A. Reed, Ramalingam Saravanan, Yohei Yamada, Colin M. Zarzycki, Pier Luigi Vidale, Jefferey A. Jonas, Naomi Henderson
Publications
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results from …
Quantifying The Sensitivity Of Maximum, Limiting, And Potential Tropical Cyclone Intensity To Sst: Observations Versus The Fsu/ Coaps Global Climate Model, Sarah Strazzo, James Elsner, Tim Larow
Quantifying The Sensitivity Of Maximum, Limiting, And Potential Tropical Cyclone Intensity To Sst: Observations Versus The Fsu/ Coaps Global Climate Model, Sarah Strazzo, James Elsner, Tim Larow
Publications
No abstract provided.
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Department of Electrical Engineering and Computer Science - Daytona Beach
This paper presents an approach to measuring computer security understood as a system property, in the category of similar properties, such as safety, reliability, dependability, resilience, etc. First, a historical discussion of measurements is presented, beginning with views of Hermann von Helmholtz in his 19th century work “Zählen und Messen”. Then, contemporary approaches related to the principles of measuring software properties are discussed, with emphasis on statistical, physical and software models. A distinction between metrics and measures is made to clarify the concepts. A brief overview of inadequacies of methods and techniques to evaluate computer security is presented, followed by …
Adjusted Tornado Probabilities, Holly M. Widen, James B. Elsner, Cameron Amrine, Rizalino B. Cruz, Erik Fraza, Laura Michaels, Loury Migliorelli, Brendan Mulholland, Michael Patterson, Sarah Strazzo, Guang Xing
Adjusted Tornado Probabilities, Holly M. Widen, James B. Elsner, Cameron Amrine, Rizalino B. Cruz, Erik Fraza, Laura Michaels, Loury Migliorelli, Brendan Mulholland, Michael Patterson, Sarah Strazzo, Guang Xing
Publications
Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, expressed as return periods, arestates, including …
Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao
Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao
Publications
Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) …
Sensitivity Of Limiting Hurricane Intensity To Sst In The Atlantic From Observations And Gcms, James Elsner, Sarah Strazzo, Thomas H. Jagger, Timothy Larow, Ming Zhao
Sensitivity Of Limiting Hurricane Intensity To Sst In The Atlantic From Observations And Gcms, James Elsner, Sarah Strazzo, Thomas H. Jagger, Timothy Larow, Ming Zhao
Publications
No abstract provided.
Frequency, Intensity, And Sensitivity To Sea Surface Temperature Of North Atlantic Tropical Cyclones In Best-Track And Simulated Data, Sarah Strazzo, James B. Elsner, Jill C. Trepanier, Kerry A. Emanuel
Frequency, Intensity, And Sensitivity To Sea Surface Temperature Of North Atlantic Tropical Cyclones In Best-Track And Simulated Data, Sarah Strazzo, James B. Elsner, Jill C. Trepanier, Kerry A. Emanuel
Publications
Synthetic hurricane track data generated from a downscaling approach are compared to best-track (observed) data to analyze differences in regional frequency, intensity, and sensitivity of limiting intensity to sea surface temperature (SST). Overall, the spatial distributions of observed and simulated hurricane counts match well, although there are relatively fewer synthetic storms in the eastern quarter of the basin. Additionally, regions of intense synthetic hurricanes tend to coincide with regions of intense observed hurricanes. The sensitivity of limiting hurricane intensity to SST computed from synthetic data is slightly lower than sensitivity computed from observed data (5.561.31 m s21 (standard error, SE) …
Sensitivity Of Limiting Hurricane Intensity To Ocean Warmth, James B. Elsner, Sarah Strazzo, Jill C. Trepanier, Thomas H. Jagger
Sensitivity Of Limiting Hurricane Intensity To Ocean Warmth, James B. Elsner, Sarah Strazzo, Jill C. Trepanier, Thomas H. Jagger
Publications
No abstract provided.