相关论文: Applications of Data Mining Techniques for Vehicul…

Mobile Ad Hoc Networks (MANETs) are decentralized wireless networks, characterized by their dynamic topologies and node mobility. In the era of cutting-edge technologies, integrating Software-Defined Networking (SDN) with MANETs offers a…

The exponential growth of textual data presents substantial challenges in management and analysis, notably due to high storage and processing costs. Text classification, a vital aspect of text mining, provides robust solutions by enabling…

Vehicular communication requires vehicles to self-organize through the exchange of periodic beacons. Recent analysis on beaconing indicates that the standards for beaconing restrict the desired performance of vehicular applications. This…

The efficient and effective monitoring of mobile networks is vital given the number of users who rely on such networks and the importance of those networks. The purpose of this paper is to present a monitoring scheme for mobile networks…

Major standardization bodies developed and designed systems that should be used in vehicular ad-hoc networks. The Institute of Electrical and Electronics Engineers (IEEE) in America designed the wireless access in vehicular environments…

Intrigued by the inherent ability of the human visual system to identify salient regions in complex scenes, attention mechanisms have been seamlessly integrated into various Computer Vision (CV) tasks. Building upon this paradigm, Vision…

Vehicular Ad Hoc Network (VANET) is a type of mobile ad hoc network (MANET) that facilitates communication among vehicles. VANET provides inter-vehicular communications to serve for the application like road traffic safety and traffic…

With the rapid advancement of Intelligent Transportation Systems (ITS) and vehicular communications, Vehicular Edge Computing (VEC) is emerging as a promising technology to support low-latency ITS applications and services. In this paper,…

How can the quality of a mobile ad hoc network (MANET) be quantified? This work aims at an answer based on the lower network layers, i.e. on connectivity between the wireless nodes, using statistical methods. A number of different quality…

Machine learning has emerged as a promising paradigm for enabling connected, automated vehicles to autonomously cruise the streets and react to unexpected situations. A key challenge, however, is to collect and select real-time and reliable…

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and…

The demand for text classification is growing significantly in web searching, data mining, web ranking, recommendation systems, and so many other fields of information and technology. This paper illustrates the text classification process…

Autonomous Vehicles (AVs) generated a plethora of data prior to support various vehicle applications. Thus, a big storage and high computation platform is necessary, and this is possible with the presence of Cloud Computing (CC). However,…

One of the important techniques of Data mining is Classification. Many real world problems in various fields such as business, science, industry and medicine can be solved by using classification approach. Neural Networks have emerged as an…

In the developing topic of smart cities, Vehicular Ad-Hoc Networks (VANETs) are crucial for providing successful interaction between vehicles and infrastructure. This research proposes a distributed Blockchain-based Vehicular Ad-hoc Network…

With a great amount of research going on in the field of autonomous vehicles or self-driving cars, there has been considerable progress in road detection and tracking algorithms. Most of these algorithms use GPS to handle road junctions and…

Vehicular ad-hoc networks (VANETs) have been proposed to automate transportation industry in order to increase its accuracy, efficiency, throughput, and specially safety. Security plays an Undeniable important role on implementing VANETs in…

Graph theory is a promising approach in handling the problem of estimating the connectivity probability of vehicular ad-hoc networks (VANETs). With a communication network represented as graph, graph connectivity indicators become valid for…

Automatic Text Categorization (TC) is a complex and useful task for many natural language applications, and is usually performed through the use of a set of manually classified documents, a training collection. We suggest the utilization of…

The work presented in this paper is part of the cooperative research project AUTO-OPT carried out by twelve partners from the automotive industries. One major work package concerns the application of data mining methods in the area of…