Download or read book Modeling of Crash Risk for Realistic Artificial Data Generation written by Lauren Hoover and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most safety performance analysis employs cross-sectional and time-series datasets, posing an important challenge to safety performance and crash modification analysis. The traditional safety model analysis paradigm relying on observed data only allows relative comparisons between analysis methods and is unable to establish how well the methods mimic the true underlying crash generation process. Assumptions are made about the data, but whether the assumptions truly characterize the safety data generation in the real world remains unknown. To address this issue, this thesis proposes the generation of realistic artificial data (RAD). In developing a prototype RAD generator for crash data, we mimic the process of crash occurrence, simulating daily traffic patterns and evaluating each trip for crash risk. For each crash, details such as crash location, crash type, and crash severity are also generated. As part of the artificial data generation, this thesis also proposes a framework for employing naturalistic driving study (NDS) data to understand and predict crash risk at a disaggregate trip level. This framework proposes a case-control study design for understanding trip level crash risk. The study also conducts a comparison of different case to control ratios and finds the model parameters estimated with these control ratios are reasonably similar. A multi-level random parameters binary logit model was estimated where multiple forms of unobserved variables were tested. This model was calibrated by modifying the constant parameter to generate a population conforming risk model, and then tested on a hold-out sample of data records. This thesis contributes to safety research through the development of a prototype RAD generator for traffic crash data, which will lead to new information about the underlying causes of crashes and ways to make roadways safer.

Download or read book Traffic Crash Modeling Considering Inconsistent Observations Interaction Behavior and Nonlinear Relationships written by Yunteng Lao and published by . This book was released on 2013 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic collisions are a worldwide issue that can cause injury and death, which leads to billions of dollars in damages every year. Significant research efforts have been undertaken to develop and utilize statistical modeling techniques for analyzing the characteristics of crash count data. While these modeling techniques have been providing meaningful outputs, improvements on these modeling methods still need to better understand the crash risk and the contributing factors. Five important issues in crash data modeling are identified in this research. The first two issues are over or under dispersion with crash data and excess zeros within crash records. Considering that they have been well studied in the previous research, this study focuses on the remaining three major issues. The first one is relevant to the partial observations of multiple processes, i.e. crash data may be collected by different agencies that create multiple data sources and may be inconsistent. A modeling mechanism that takes advantage of all datasets for better estimation results is highly desirable. The second one is an interaction issue. Some collisions are single vehicle crashes, such as off-road crashes and rollover incidents, and some collisions involve interaction behavior, such as the Animal-Vehicle Collision (AVC) and the Vehicle-Vehicle Collision. The characteristics of crashes with interaction behavior are different from those with only one vehicle involved. It is challenging to develop a crash modeling scheme that can capture the interaction behavior. The last one is the nonlinear relationship issue. Most previous collision models are Generalized Linear Model-based (GLM-based) approaches. Such GLM-based approaches are constrained by their linear model specifications because, in most situations, the relationship between the crash rate and its contributing factors are not linear or may not even be monotonic. Thus, finding a way to model the collision data with nonlinear and non-monotonic relationships is of utmost importance. To address the issues of inconsistent observations, two techniques are developed. A fuzzy logic-based data mapping algorithm is proposed as the first technique to match data from two datasets so that duplicate crash records can be removed when combining these datasets. The membership functions of the fuzzy logic algorithm are established based on survey inputs collected from experts of the Washington State Department of Transportation (WSDOT). As verified by expert judgment collected through another survey, the accuracy of this algorithm was approximately 90%. Applying this algorithm to the two WSDOT datasets relevant to AVC, reported AVC data and the Carcass Removal (CR) data, the combined dataset has 15% -22% more records compared to the original CR dataset. The proposed algorithm is proven effective for merging the Reported AVC data and the CR data, with a combined dataset being more complete for wildlife safety studies and countermeasure evaluations. The second technique is a diagonal inflated bivariate Poisson regression (DIBP) method. It is an inflated version of bivariate Poisson regression model adopted to directly fit two datasets together. The proposed model technique was also applied to the reported AVC and CR data sets collected in Washington State between 2002 and 2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over- dispersed data sets. Compared with three other types of models; double Poisson, bivariate Poisson, and zero-inflated double Poisson; the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two datasets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers another new approach to investigating paired data sources from a different perspective. To address the issues with the interaction issue, a new occurrence mechanism-based probability model, an interaction-based model, which explicitly formulates the interactions between the objects, is introduced. The proposed method was applied to the AVC data and this method can explicitly formulate the interactions between animals and drivers to better capture the relationships among drivers' and animals' attributes, roadway and environmental factors, and AVCs. Findings of this study show that the proposed occurrence mechanism-based probability model better capture the impact of drivers' and animals' attributes on the AVC. This method can be further developed to model other types of collisions with interaction behavior. To address the nonlinear relationship issue, a Generalized Nonlinear Model (GNM)-based approach is put forward. The GNM-based approach is developed to utilize a nonlinear regression function to better elaborate non-monotonic relationships between the independent and dependent variables. Previous studies focused mainly on causal factor identification and crash risk modeling using Generalized Linear Models (GLMs), such as Poisson regression, and logistic regression among others. However, their basic assumption of a generalized linear relationship between the dependent variable (for example, crash rate) and independent variables (for example, contributing factors to crashes) established via a link function can often be violated in reality. Consequently, the GLM-based modeling results could provide biased findings and conclusions when the contributing factors have parabolic impact on the crashes. In this research, a GNM-based approach is applied with the rear end accident data and the AVC data collected from ten highway routes starting in 2002 and ending in 2006. For the rear-end collision application, the results show that truck percentage and grade have a parabolic impact: both items increase crash risks initially, but decrease risks after certain thresholds. Similarly, Annual Average Daily Traffic (AADT) and grade also have a parabolic impact on the AVC rate. Such non-monotonic relationships cannot be captured by regular GLM's, which further demonstrates the flexibility of GNM-based approaches in modeling the nonlinear relationship among data and providing more reasonable explanations. The superior GNM-based model interpretations better explain the parabolic impacts of some specific contributing factors and help in selecting and evaluating rear-end crash safety improvement plans. In Summary, these solutions proposed to address the three major issues in crash modeling are important for crash studies. The fuzzy-logic based data mapping algorithm can combine partial observations from different processes to form up a more complete dataset for a thorough analysis. The diagonal inflated bivariate Poisson models can directly take two data observation processes into account. The occurrence mechanism based probability models and GNM based models are effective methods for handling the interaction issue and non-linear relationships between dependent and independent variables.

Download or read book Machine Learning for Financial Risk Management with Python written by Abdullah Karasan and published by "O'Reilly Media, Inc.". This book was released on 2021-12-07 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how to compare results from ML models with results obtained by traditional financial risk models. Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models. Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Revisit and improve market risk models (VaR and expected shortfall) using machine learning techniques Develop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML models Capture different aspects of liquidity with a Gaussian mixture model Use machine learning models for fraud detection Identify corporate risk using the stock price crash metric Explore a synthetic data generation process to employ in financial risk.

Download or read book Modeling of Road Traffic Events written by Jerzy Kisilowski and published by Springer. This book was released on 2022-01-02 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This books reviews and brings readers up to date with the latest research knowledge on road traffic safety. It describes and discusses mathematical descriptions of the process of a motor vehicle crash and indicates the various factors that impact on collision models. It tackles also vehicle stability and shows how the forces generated in crashes result in different extents of post-accident repair. Mathematical models that simulate vehicle stability data are compared with those of real vehicles. Practical uses of the models are explained to readers. The book will be of interest to researchers in transport and vehicle technology well as automotive industry professionals.

Download or read book After the Crash written by Sharyn O'Halloran and published by Columbia University Press. This book was released on 2019-10-08 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2008 crash was the worst financial crisis and the most severe economic downturn since the Great Depression. It triggered a complete overhaul of the global regulatory environment, ushering in a stream of new rules and laws to combat the perceived weakness of the financial system. While the global economy came back from the brink, the continuing effects of the crisis include increasing economic inequality and political polarization. After the Crash is an innovative analysis of the crisis and its ongoing influence on the global regulatory, financial, and political landscape, with timely discussions of the key issues for our economic future. It brings together a range of experts and practitioners, including Joseph Stiglitz, a Nobel Prize winner; former congressman Barney Frank; former treasury secretary Jacob Lew; Paul Tucker, a former deputy governor of the Bank of England; and Steve Cutler, general counsel of JP Morgan Chase during the financial crisis. Each poses crucial questions: What were the origins of the crisis? How effective were international and domestic regulatory responses? Have we addressed the roots of the crisis through reform and regulation? Are our financial systems and the global economy better able to withstand another crash? After the Crash is vital reading as both a retrospective on the last crisis and an analysis of possible sources of the next one.

Download or read book Artificial Intelligence in Asset Management written by Söhnke M. Bartram and published by CFA Institute Research Foundation. This book was released on 2020-08-28 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Download or read book Cloud Native Application Protection Platforms written by Russ Miles and published by "O'Reilly Media, Inc.". This book was released on 2024-09-13 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud native security isnâ??t a game for individual players. It requires team collaboration with a platform that can help cloud security engineers, developers, and operations people do their best work. Thatâ??s what the cloud native application protection platform (CNAPP) delivers. With this practical guide, youâ??ll learn how CNAPPs can help you consolidate security through DevSecOps across cloud native technologies, practices, and application lifecycles. Through real-life attack scenarios, authors Russ Miles, Steve Giguere, and Taylor Smith help you explore how CNAPP not only mitigates multidimensional threats, but also reduces complexity and helps your team stay one step ahead of attackers. CNAPP provides a holistic approach to your cloud native development across identities, workloads, networks, and infrastructure. With this book, you will: Examine threats to different parts of the cloud native stack, including pipelines, supply chains, infrastructure, workloads, and applications Learn what CNAPP is and how it enables the context-sharing and collaboration necessary to secure your applications from development to runtime Assess your own attack surface from a code and runtime standpoint Identify blind spots in your existing cloud native security coverage Leverage CNAPP to achieve a holistic, collaborative security environment

Download or read book The Mind s Mirror Risk and Reward in the Age of AI written by Daniela Rus and published by W. W. Norton & Company. This book was released on 2024-08-06 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exciting introduction to the true potential of AI from the director of MIT’s Computer Science and Artificial Intelligence Laboratory. Imagine a technology capable of discovering new drugs in days instead of years, helping scientists map distant galaxies and decode the language of whales, and aiding the rest of us in mundane daily tasks, from drafting email responses to preparing dinner. Now consider that this same technology poses risks to our jobs and society as a whole. Artificial Intelligence is no longer science fiction; it is upending our world today. As advances in AI spark fear and confusion, The Mind’s Mirror reminds us that in spite of the very real and pressing challenges, AI is a force with enormous potential to improve human life. Computer scientist and AI researcher Daniela Rus, along with science writer Gregory Mone, offers an expert perspective as a leader in the field who has witnessed many technological hype cycles. Rus and Mone illustrate the ways in which AI can help us become more productive, knowledgeable, creative, insightful, and even empathetic, along with the many risks associated with misuse. The Mind’s Mirror shows readers how AI works and explores what we, as individuals and as a society, must do to mitigate dangerous outcomes and ensure a positive impact for as many people as possible. The result is an accessible and lively exploration of the underlying technology and its limitations and possibilities—a book that illuminates our possible futures in the hopes of forging the best path forward.

Download or read book Applications of Machine Learning written by Prashant Johri and published by Springer Nature. This book was released on 2020-05-04 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Download or read book Pricing and Risk Management of Synthetic CDOs written by Anna Schlösser and published by Springer Science & Business Media. This book was released on 2011-02-04 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the generation of scenarios for the complete universe of risk factors and the inclusion of CDO structures in a portfolio context. For this objective, it is especially important to have a computationally fast model that can also be used in a scenario simulation framework. The well known Gaussian copula model is extended in various ways in order to improve its drawbacks of correlation smile and time inconsistency. Also the application of the large homogeneous cell assumption, that allows to differentiate between rating classes, makes the model convenient and powerful for practical applications. The Crash-NIG extension introduces an important regime-switching feature allowing the possibility of a market crash that is characterized by a high-correlation regime.

Download or read book Frontiers in Cardiovascular Medicine Rising Stars 2022 written by Liqiu Yan and published by Frontiers Media SA. This book was released on 2024-05-01 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are delighted to present the inaugural Frontiers in Cardiovascular Medicine “Rising Stars” article collection. This collection showcases the high-quality work of internationally recognized researchers in the early stages of their independent careers. All Rising Star researchers were individually nominated by the Chief Editors of the Journal in recognition of their potential to influence the future directions in their respective fields. The work presented here highlights the diversity of research performed across the entire breadth of cardiovascular medicine, including the elucidation of fundamental biology, the development of novel diagnostics or therapeutics, computational modelling approaches, and bioengineering strategies for regeneration.

Download or read book Measurement Error written by John P. Buonaccorsi and published by CRC Press. This book was released on 2010-03-02 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu

Download or read book Distributed Computing and Artificial Intelligence 17th International Conference written by Yucheng Dong and published by Springer Nature. This book was released on 2020-08-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together past experience, current work and promising future trends associated with distributed computing, artificial intelligence and their application in order to provide efficient solutions to real problems. DCAI 2020 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program will present both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 83 papers were submitted to main track and special sessions, by authors from 26 different countries representing a truly “wide area network” of research activity. The DCAI’20 technical program has selected 35 papers and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the University of L'Aquila (Italy). We would like to thank all the contributing authors, the members of the Program Committee and the sponsors (IBM, Armundia Group, EurAI, AEPIA, APPIA, CINI, OIT, UGR, HU, SCU, USAL, AIR Institute and UNIVAQ).

Download or read book Chance Discoveries in Real World Decision Making written by Yukio Ohsawa and published by Springer Science & Business Media. This book was released on 2006-09-06 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc. The methods presented in this book are based on the interaction of human, machine, and human's living environment, rather than based purely automated predictions of the future. This is a promising direction of computer-supported decision of human in a radically changing environment.

Download or read book Heterogeneous Data Management Polystores and Analytics for Healthcare written by El Kindi Rezig and published by Springer Nature. This book was released on 2023-01-20 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2022, and the 8th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2022, which were held virtually on September 9, 2022. The proceedings include 3 full papers each from Poly 2022 and from DMAH 2022. DMAH deals with innovative data management and analytics technologies highlighting end-to-end applications, systems, and methods to address problems in healthcare, public health, and everyday wellness, with clinical, physiological, imaging, behavioral, environmental, and omic - data, and data from social media and the Web. Poly is focusing on the broader real-world polystore problem, which includes data management, data integration, data curation, privacy, and security.

Download or read book Proceedings written by and published by . This book was released on 1996 with total page 1168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Hybrid Artificial Intelligent Systems written by Héctor Quintián and published by Springer Nature. This book was released on with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: