Download or read book Modeling Highway Traffic Safety in Nigeria Using Bayesian Network written by Anthony Cyril Mbakwe and published by . This book was released on 2011 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Intelligent Systems and Applications written by Yaxin Bi and published by Springer Nature. This book was released on 2019-08-23 with total page 1312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a remarkable collection of chapters covering a wide range of topics in the areas of intelligent systems and artificial intelligence, and their real-world applications. It gathers the proceedings of the Intelligent Systems Conference 2019, which attracted a total of 546 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-review process, after which 190 were selected for inclusion in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have made it possible to tackle a host of problems more effectively. This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for an international conference as a venue for reporting on the latest innovations and trends. This book collects both theory and application based chapters on virtually all aspects of artificial intelligence; presenting state-of-the-art intelligent methods and techniques for solving real-world problems, along with a vision for future research, it represents a unique and valuable asset.

Download or read book Predictive Accident Modeling for Highway Transportation System Using Bayesian Networks written by Dan Chen and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The highway network, as a critical infrastructure in our daily life, is an important component of the public transportation system. In the face of a continuously increasing highway accident rate, highway safety is certainly one of the greatest concerns for transportation departments worldwide. To better improve the current situation, several studies have been carried out on preventing the occurrence of highway accidents or reducing the severity level of highway accidents. The principal causes of highway accidents can be summarized into four categories: external environment conditions, operational environment conditions, driver conditions and vehicle conditions. This research proposes a representational Bayesian Networks (BNs) model which can predict and continuously update the likelihood of highway accidents, by considering a set of well-defined variables belonging to these principal causes, also named risk factors, which directly or indirectly contribute to the frequency and severity of highway accidents. This accident predictive BNs model is developed using accidents data from Transport Canada's National Collision Database (NCDB) during the period of 1999 to 2010. Model testing is provided with a case study of Highway #63 site, which is from 6 km southwest of Radway to 16 km north of Fort Mackay in north Alberta, Canada. The validity of this BNs model is established by comparing prediction results with relevant historical records. The positive outcome of this exercise presents great potential of the proposed model to real life applications. Furthermore, this predictive BNs accident model can be integrated with a Safety Instrumented System (SIS). This integration would assist in predicting the real-time probability of accident and would also help activating risk management actions in a timely fashion. This research also simulates 10 scenarios with different specific states of variables to predict the probability of fatal accident occurrence, which demonstrates how the BNs model is integrated with SIS. The major objective of this research is to introduce the predictive accident BNs model with the capabilities of inferring the dependent causal relations and predicting the probability of highway accidents. It is also believed that this BNs model would help developing efficient and effective transportation risk management strategies.

Download or read book Construction Health and Safety in Developing Countries written by Patrick Manu and published by Routledge. This book was released on 2019-08-22 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The global construction sector is infamous for high levels of injuries, accidents and fatalities, and poor health and well-being of its workforce. While this record appears in both developed and developing countries, the situation is worse in developing countries, where major spending on infrastructure development is expected. There is an urgent need to improve construction health and safety (H&S) in developing countries. The improvement calls for the development of context-specific solutions underpinned by research into challenges and related solutions. This edited volume advances the current understanding of construction H&S in developing countries by revealing context-specific issues and challenges that have hitherto not been well explored in the literature, and applying emergent H&S management approaches and practices in developing countries. Coverage includes countries from the regions of sub-Saharan Africa, Latin America, Asia and Europe. This book, which is the first compendium of research into construction H&S issues in developing countries, adds considerable insight into the field and presents innovative solutions to help address poor H&S in construction in developing nations. It is a must read for all construction professionals, researchers and practitioners interested in construction and occupational H&S, safety management, engineering management and development studies.

Download or read book Modeling Multilevel Data in Traffic Safety written by Hoong Chor Chin and published by Nova Science Publishers. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background: In the study of traffic system safety, statistical models have been broadly applied to establish the relationships between the traffic crash occurrence and various risk factors. Most of the existing methods, such as the generalised linear regression models, assume that each observation (e.g. a crash or a vehicle involvement) in the estimation procedure corresponds to an individual situation. Hence, the residuals from the models exhibit independence. Problem: However, this "independence" assumption may often not hold true since multilevel data structures exist extensively because of the data collection and clustering process. Disregarding the possible within-group correlations may lead to production of models with unreliable parameter estimates and statistical inferences. Method: Following a literature review of crash prediction models, this book proposes a 5 T-level hierarchy, viz. (Geographic region level -- Traffic site level -- Traffic crash level -- Driver-vehicle unit level -- Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To model properly the potential between-group heterogeneity due to the multilevel data structure, a framework of hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is employed. Bayesian inference using Markov chain Monte Carlo algorithm is developed to calibrate the proposed hierarchical models. Two Bayesian measures, viz. the Deviance Information Criterion and Cross-Validation Predictive Densities, are adapted to establish the model suitability. Illustrations: The proposed method is illustrated using two case studies in Singapore: 1) a crash-frequency prediction model which takes into account Traffic site level and Time level; 2) a crash-severity prediction model which takes into account Traffic crash level and Driver-vehicle unit level. Conclusion: Comparing the predictive abilities of the proposed models against those of traditional methods, the study demonstrates the importance of accounting for the within-group correlations and illustrates the flexibilities and effectiveness of the Bayesian hierarchical approach in modelling multilevel structure of traffic safety data.

Download or read book Modeling Highway Crashes Using Bayesian Belief Networks Technique and GIS written by Thobias M. Sando and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evaluating Traffic Safety Network Screening written by Michael David Pawlovich and published by . This book was released on 2003 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highway crashes result in over 40,000 deaths per year (500,000 worldwide). Their impact on the national economy is estimated at more than 230 billion dollars. Highway safety is the top priority of the United States Department of Transportation (US DOT). Funds dedicated to the problem are expected to increase substantially. Highway safety is a multidisciplinary issue. An important tool is the safety improvement candidate location (SICL) list. SICL lists list high crash locations for potential mitigation. SICL lists are developed using crash data. Crash frequency, rate, or loss is used to rank the worst locations. Classical statistical techniques are applied. In some cases, simple frequency analyses are used to draw attention to "problem" locations. Simple ranked lists suffer from methodological and practical limitations. Chief among these is the inability to identify "sites with promise", sites where mitigation has the best chance of success. Agencies representing engineering and enforcement generally examine top sites prior to resource dedication. This is resource intensive and efforts of different safety interests are often not well coordinated. For over 20 years, empirical Bayesian (EB) has been proposed to address these limitations. EB identifies sites where mitigation might be most effective, increases estimate confidence, and provides information on relative site safety. EB is being widely implemented at the national level. State and local agencies continue SICL development based on long-standing procedures. EB allows decision makers to more reliably estimate the crash reduction potential at specific sites. However, EB requires development of safety performance functions for road type classes. The technique also requires a priori development of accident modification factors. These requirements add significant expense. Powerful computers and advanced statistical sampling techniques allow hierarchical Bayesian statistics to be applied to highway safety. Hierarchical Bayesian eliminates the need for a priori functions and factors. This approach can readily incorporate additional information. It can also explicitly identify important relationships between causal factors and safety performance. The approach uses data to define results, based on an analyst-specified level of uncertainty. This dissertation discusses SICL list development and evaluates the potential of Bayesian statistics to improve their utility.

Download or read book A Full Bayes Approach to Road Safety written by Mohammad Heydari and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Big Data Analytics for Smart Transport and Healthcare Systems written by Saeid Pourroostaei Ardakani and published by Springer Nature. This book was released on 2024-01-04 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to introduce big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems. It focuses on machine learning techniques and data processing approaches which have the capacity to handle/process huge, live, and complex datasets in real-time transportation and healthcare applications. For this, several state-of-the-art data processing approaches including data pre-processing, classification, regression, and clustering are introduced, tested, and evaluated to highlight their benefits and constraints where data is sensitive, real-time, and/or semi-structured.

Download or read book Predictive Accident Modeling Through Bayesian Network written by Md. Al-Amin Baksh and published by . This book was released on 2013 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Information Processing written by Biao Luo and published by Springer Nature. This book was released on 2023-11-26 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 1274 papers presented in the proceedings set were carefully reviewed and selected from 652 submissions. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements.

Download or read book Proceedings of the Canadian Society of Civil Engineering Annual Conference 2021 written by Scott Walbridge and published by Springer Nature. This book was released on 2022-06-02 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the proceedings of the Annual Conference of the Canadian Society of Civil Engineering 2021. The contents of this volume focus on specialty conferences in construction, environmental, hydrotechnical, materials, structures, transportation engineering, etc. This volume will prove a valuable resource for those in academia and industry.

Download or read book Computational Science and Its Applications ICCSA 2021 written by Osvaldo Gervasi and published by Springer Nature. This book was released on 2021-09-11 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​The ten-volume set LNCS 12949 – 12958 constitutes the proceedings of the 21st International Conference on Computational Science and Its Applications, ICCSA 2021, which was held in Cagliari, Italy, during September 13 – 16, 2021. The event was organized in a hybrid mode due to the Covid-19 pandemic.The 466 full and 18 short papers presented in these books were carefully reviewed and selected from 1588 submissions. Part X of the set includes the proceedings of the following workshops: ​International Workshop on Smart and Sustainable Island Communities (SSIC 2021); International Workshop on Science, Technologies and Policies to Innovate Spatial Planning (STP4P 2021); International Workshop on Sustainable Urban Energy Systems (SUREN-SYS 2021); International Workshop on Ports of the future - smartness and sustainability (SmartPorts 2021); International Workshop on Smart Tourism (SmartTourism 2021); International Workshop on Space Syntax for Cities in Theory and Practice (Syntax_City 2021); International Workshop on Theoretical and Computational Chemistryand its Applications (TCCMA 2021); International Workshop on Urban Form Studies (UForm 2021); International Workshop on Urban Space Accessibility and Safety (USAS2021); International Workshop on Virtual and Augmented Reality and Ap-plcations (VRA 2021); International Workshop on Advanced and Computational Methods for Earth Science applications (WACM4ES 2021).

Download or read book Transportation Safety Data and Analysis written by Grant G. Schultz and published by . This book was released on 2010 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent research suggests that traditional safety evaluation methods may be inadequate in accurately determining the effectiveness of roadway safety measures. In recent years, advanced statistical methods are being utilized in traffic safety studies to more accurately determine the effectiveness of roadway safety measures. These methods, particularly Bayesian statistical techniques, have the capabilities to account for the shortcomings of traditional methods. Hierarchical Bayesian modeling is a powerful tool that more fully identifies a given problem than a simpler model could. This report explains the process wherein a hierarchical Bayesian model is developed as a tool to analyze the effectiveness of two types of road safety measures: raised medians and cable barrier. Several sites where these safety measures have been implemented in the last 10 years were evaluated using available crash data. The results of this study show that the installation of a raised median is an effective technique to reduce the overall crash frequency and crash severity on Utah roadways. The analysis of cable barrier systems shows that they are effective in decreasing cross-median crashes and crash severity. The tool developed through the research can now be utilized for additional analyses, including hot-spot analysis, before-after change, and general safety modeling. This tool will be an asset to the Utah Department of Transportation Traffic and Safety Division for data analysis in the years to come.

Download or read book Intelligence Science and Big Data Engineering Big Data and Machine Learning written by Zhen Cui and published by Springer Nature. This book was released on 2019-11-28 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.

Download or read book Machine Learning Techniques for Smart City Applications Trends and Solutions written by D. Jude Hemanth and published by Springer Nature. This book was released on 2022-09-19 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with innovative solutions in the above-mentioned issues with the purpose of alleviating the pressing needs of human society. This book includes content with practical examples which are easy to understand for readers. It also covers a multi-disciplinary field and, consequently, it benefits a wide readership including academics, researchers, and practitioners.

Download or read book Artificial Intelligence based Internet of Things Systems written by Souvik Pal and published by Springer Nature. This book was released on 2022-01-11 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects.