János Tóth, Domokos Esztergár-Kiss

Smart City


Classification

Classification could be used to recognize individual activity, social event, and region semantics. It is a technique that identifies the class to which each sample belongs, with a model learned from a training set of samples with their class labels. For example, when recognizing individual activity from trace data, each trace is a sample, and each type of activity is a class. Most classification algorithms have three stages: feature extraction, training procedure, and test procedure. The features extracted and the models used for training are most important for classification.

Smart City

Tartalomjegyzék


Kiadó: Akadémiai Kiadó

Online megjelenés éve: 2019

ISBN: 978 963 454 271 1

This course material is included in the BME Faculty of Transportation Engineering and Vehicle Engineering Master programme. The main topics of Smart City course are the followings: Paradigm shift in urban citizen’s life, Smart city introduction, definitions and evaluation methods, Land use functions and models, city planning and strategic aspects, Utilization possibilities of information from social media, Internet of Things, wireless sensor networks and Smart Grid applications, Intermodal connections with their functionalities in the Smart City, Smart solutions in transportation management, Hungarian and international best practices.

Hivatkozás: https://mersz.hu/toth-esztergar-kiss-smart-city//

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