عنوان

Traffic mining applied to police activities :

شابک

3319756087

شابک

9783319756080

شابک اشتباه

3319756079

شابک اشتباه

9783319756073

عنوان اصلي

Traffic mining applied to police activities :

نام عام مواد

[Book]

ساير اطلاعات عنواني

proceedings of the 1st Italian Conference for the Traffic Police (TRAP- 2017) /

نام نخستين پديدآور

Fabio Leuzzi, Stefano Ferilli, editors.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2018]

تاریخ نشرو بخش و غیره

©2018

نام خاص و کميت اثر

1 online resource

عنوان فروست

Advances in intelligent systems and computing,

مشخصه جلد

volume 728

شاپا ي ISSN فروست

2194-5357 ;

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

Intro; Foreword; Preface; Organization; Executive Committee; Program Committee; Organizing Committee; Sponsoring Institutions; Contents; Part I Invited Talks; Data and Analytics Framework. How Public Sector Can Profit from Its Immense Asset, Data; 1 Introduction; 2 Big Data Analytics for the Public Administration; 3 Big Data and Public Policy; 4 Data and Analytics Framework for the Public Administration; 5 Services Provided by the DAF; 6 Architectural Design Highlights; 7 Conclusions; References; Advancements in Mobility Data Analysis; 1 Big Mobility Data Sources.

متن يادداشت

2 Collective Mobility Data Analysis3 Individual Mobility Data Analysis; 4 Mobility Data-Driven Applications and Services; 5 Conclusions; References; Part II Technical Contributions; Towards a Pervasive and Predictive Traffic Police; 1 Introduction; 2 Research Fields: Background and Challenges; 2.1 Mining Traffic Data; 2.2 Hints of Vehicle Forensics and Analytics; 2.3 Mining Patrolling Data; 2.4 Mining Information Exchange Among Control Rooms; 3 An Integrated Approach to Road Understanding and Event Management; 4 Conclusions; References.

متن يادداشت

3.1 A Real Case of Study in Mijas (Spain)3.2 Actual Results; 3.3 Other Results; 4 Practical Applications; 5 Conclusions and Future Work; References; Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset; 1 Introduction; 2 Statistical Analysis; 3 Design of a Plates Behavior Classifier; 3.1 Overview; 3.2 The Tool; 4 Our Findings; 4.1 Tuning the Classifier; 4.2 Classifying Routes; 4.3 Classifying Plates; 5 Related Work; 5.1 Traffic Monitoring and Analysis; 5.2 Pattern Mining and Clusterization; 6 Conclusions and Future Work; References.

متن يادداشت

4.2 Second Profile5 Conclusions and Future Work; References; Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion; 1 Introduction; 2 Related Works; 3 Proposed Method; 3.1 Dynamic Tensor Model for Traffic Flow; 3.2 Fast Dynamic Tensor Completion; 4 Experimental Evaluation; 4.1 Experiment Settings; 4.2 Experiment Results; 5 Conclusion; References; Reducing the Risk of Accidents with Not Insured British Vehicles in Southern Spain; 1 Introduction; 2 Methodology; 2.1 Collecting the Samples; 2.2 Weakness; 3 Results and Discussion.

متن يادداشت

A Process Mining Approach to the Identification of Normal and Suspect Traffic Behavior1 Introduction; 2 The WoMan Framework; 2.1 Input Formalism; 2.2 Output Formalism; 3 Workflow Supervision and Prediction; 4 Proposal for Application to Traffic Understanding; 4.1 Setting; 4.2 Motivation; 4.3 Example; 5 Conclusions and Future Work; References; Detecting Criminal Behaviour Patterns in Spain and Italy Using Formal Concept Analysis; 1 Introduction; 2 Formal Concept Analysis; 3 Criminal Behaviour Patterns in Southern Spain; 4 Analysing Datasets of Traffic Cameras; 4.1 First Profile.

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

This book presents high-quality original contributions on the development of automatic traffic analysis systems that are able to not only anticipate traffic scenarios, but also understand the behavior of road users (vehicles, bikes, trucks, etc.) in order to provide better traffic management, prevent accidents and, potentially, identify criminal behaviors. Topics also include traffic surveillance and vehicle accident analysis using formal concept analysis, convolutional and recurrent neural networks, unsupervised learning and process mining. The content is based on papers presented at the 1st Italian Conference for the Traffic Police (TRAP), which was held in Rome in October 2017. This conference represents a targeted response to the challenges facing the police in connection with managing massive traffic data, finding patterns from historical datasets, and analyzing complex traffic phenomena in order to anticipate potential criminal behaviors. The book will appeal to researchers, practitioners and decision makers interested in traffic monitoring and analysis, traffic modeling and simulation, mobility and social data mining, as well as members of the police.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783319756080

شماره استاندارد بين المللي کتاب و موسيقي

9783319756073

موضوع مستند نشده

Data mining in law enforcement, Congresses.

موضوع مستند نشده

Social sciences-- Methodology, Congresses.

موضوع مستند نشده

COMPUTERS-- Database Management-- Data Mining.

موضوع مستند نشده

Data mining in law enforcement.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

Highway & traffic engineering.

موضوع مستند نشده

Network hardware.

موضوع مستند نشده

Operational research.

موضوع مستند نشده

Social sciences-- Methodology.

موضوع مستند نشده

COM-- 021030

موضوع مستند نشده

UKN

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Ferilli, Stefano

مستند نام اشخاص تاييد نشده

Leuzzi, Fabio

مستند نام تنالگان تاييد نشده

Italian Conference for the Traffic Police(1st :2017 :, Rome, Italy)

تاريخ عمليات

20200823110121.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y