Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators wi...
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With the rapid development of China's economy and the continuous improvement of people's living standards, the public's travel demand is increasing. However, rapid traffic demand growth is bound to bring p...
ISBN:
(数字)9781728170817
ISBN:
(纸本)9781728170824
With the rapid development of China's economy and the continuous improvement of people's living standards, the public's travel demand is increasing. However, rapid traffic demand growth is bound to bring problems such as traffic congestion and traffic accidents. Accurate travel speed prediction can provide a basis for traveler route selection and traffic guidance. This study uses the Beidou positioning navigation system data to take the Shanghai-Kunming freeway section in Jiangxi Province as a test section to study the travel speed prediction. The contents include:(1) Summarizing the main methods of short-term traffic flow prediction. (2) Design the preprocessing process for Beidou system data. (3) A travel speed prediction model based on support vector regression is established. (4) The SVR model is used to conduct empirical prediction research on different traffic flow states.
Measuring the interaction between cities is an important research topic in many disciplines, such as sociology, geography, economics and transportation science. The traditional and most widely used spatial interaction...
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In this study, we deal with the simulation problem of ship-tugging operations in a large container port. First, we build a tugboat-service network using a directed graph, where the nodes consist of tugboat bases, anch...
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Unmanned Aerial Vehicles (UAVs) possess high mobility and flexible deployment capabilities, prompting the development of UAVs for various application scenarios within the Internet of Things (IoT). The unique capabilit...
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With the continuous increase of IoT devices, multiple devices desire to use network resources simultaneously during peak hours and overload conditions, leading to collisions and a reduction in the network’s effective...
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ISBN:
(数字)9798331517786
ISBN:
(纸本)9798331517793
With the continuous increase of IoT devices, multiple devices desire to use network resources simultaneously during peak hours and overload conditions, leading to collisions and a reduction in the network’s effective throughput. The Access Class Barring (ACB) method has been proposed as the optimal potential solution in LTE communication networks to overcome this problem. However, existing ACB schemes do not fully utilize preamble resources, and most schemes do not consider the situation where PUSCH resources are limited. Therefore, this paper proposes a two-stage ACB algorithm that considers the situation of limited PUSCH resources. This algorithm recycles part of the preamble resources and sets the ACB factor based on the number of PUSCH resources. Simulation results show that our proposed algorithm significantly outperforms traditional schemes in terms of total service time, delay, throughput, and PUSCH resource efficiency.
Nowadays, with advanced information technologies deployed citywide, large data volumes and powerful computational resources are intelligentizing modern city development. As an important part of intelligent transportat...
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With the digitization of modern cities, large data volumes and powerful computational resources facilitate the rapid update of intelligent models deployed in smart cities. Continual learning (CL) is a novel machine le...
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Cycling is a green transportation mode, and is promoted by many governments to mitigate traffic congestion. However, studies concerning the traffic dynamics of bicycle flow are very limited. This study experimentally ...
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Device activity detection and channel estimation are central problems in massive Machine Type Communication (mMTC) scenarios. Given the sparse distribution of active devices, compressive sensing (CS) emerges as a viab...
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ISBN:
(数字)9798331517786
ISBN:
(纸本)9798331517793
Device activity detection and channel estimation are central problems in massive Machine Type Communication (mMTC) scenarios. Given the sparse distribution of active devices, compressive sensing (CS) emerges as a viable solution at the gNB to mitigate interference stemming from non-orthogonal preamble sets. This paper proposes an algorithm for optimizing measurement matrix, thereby elevating the performance of signal recovery in CS. Within the proposed algorithm, a optimization model that integrates eigenvalue averaging and equiangular tight frame (ETF) theory is formulated, and an iterative algorithm is devised to approximate the optimal solution utilizing singular value decomposition (SVD). Further, a weight-based strategie is discussed with respect to the feasibility of the proposed algorithm, accompanied by the introduction of iteration termination condition. Experimental results corroborate the algorithm’s swift convergence, underpinning the efficient production of high-performance matrices that refine the accuracy of joint device activity detection and channel estimation.
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