Francisco Pereira – författare

Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility 'structural' analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena.

This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data's impact on mobility and an introduction to the tools necessary to apply new techniques.

The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.

Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data

Mobility Patterns, Big Data and Transport Analytics provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications and concepts in mobility analysis and transportation systems. Users will find a detailed, mobility ''structural'' analysis and a look at the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications and transportation systems analysis that are related to complex processes and phenomena.This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data''s impact on mobility and an introduction to the tools necessary to apply new techniques.The book covers in detail, mobility ''structural'' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data''s impact on mobility, and an introduction to the tools necessary to apply new techniques.- Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics- Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends- Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field- Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach- Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data

Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling, Second Edition provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing, and controlling mobility patterns-a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications, and concepts in mobility analysis and transportation systems. Fields covered are evolving rapidly, and this new edition updates existing material and provides new chapters that reflect recent developments in the field (such as the emergence of active, transfer and reinforcement learning).Users will find a detailed, mobility ‘structural’ analysis and a look at the extensive behavioral characteristics of transport, observability requirements, limitations for realistic transportation applications, and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data’s impact on mobility and an introduction to the tools necessary to apply new techniques.Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analyticsCovers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trendsDelivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the fieldFeatures a companion website with videos showing analyses performed, as well as test codes and data-sets, thus allowing readers to recreate and apply highlighted techniques to their own data

Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling, Second Edition provides a guide to the new analytical framework and its relation to big data, focusing on capturing, predicting, visualizing, and controlling mobility patterns-a key aspect of transportation modeling. The book features prominent international experts who provide overviews on new analytical frameworks, applications, and concepts in mobility analysis and transportation systems. Fields covered are evolving rapidly, and this new edition updates existing material and provides new chapters that reflect recent developments in the field (such as the emergence of active, transfer and reinforcement learning).Users will find a detailed, mobility 'structural' analysis and a look at the extensive behavioral characteristics of transport, observability requirements, limitations for realistic transportation applications, and transportation systems analysis that are related to complex processes and phenomena. This book bridges the gap between big data, data science, and transportation systems analysis with a study of big data's impact on mobility and an introduction to the tools necessary to apply new techniques. - Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics- Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends- Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field- Features a companion website with videos showing analyses performed, as well as test codes and data-sets, thus allowing readers to recreate and apply highlighted techniques to their own data

This book constitutes the refereed proceedings of the 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, held in Coimbra, Portugal, in September 2015. The 45 revised full papers presented together with 36 revised short papers were carefully reviewed and selected from a total of 131 submissions. EPIA 2015, following the standard EPIA format, covers a wide range of AI topics as follows: ambient intelligence and affective environments, artificial Intelligence in medicine, artificial intelligence in transportation systems, artificial life and evolutionary algorithms, computational methods in bioinformatics and systems biology, general artificial intelligence, intelligent information systems, intelligent robotics, knowledge discovery and business intelligence, multi-agent systems: theory and applications, social simulation and modelling, text mining and applications.