Zobrazeno 1 - 10
of 461
pro vyhledávání: '"passenger flow prediction"'
Publikováno v:
Chengshi guidao jiaotong yanjiu, Vol 27, Iss 9, Pp 91-96 (2024)
Objective Accurate short term passenger flow prediction is of great significance to improve the operation and management efficiency of the ultra-large scale of urban rail transit network. However, the current research on deep exploration of the spati
Externí odkaz:
https://doaj.org/article/236a2b0de040444cbd3c121c42055c5d
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 7, Pp 1879-1888 (2024)
Bus passenger flow prediction is a crucial issue of public transportation planning and management. Though spatio-temporal graph convolution has shown promising results for subway passenger flow prediction, the existing spatial modeling methods based
Externí odkaz:
https://doaj.org/article/09644b45caac4dcb8db468291e43e9e5
Publikováno v:
In Knowledge-Based Systems 25 November 2024 304
Publikováno v:
IEEE Access, Vol 12, Pp 95196-95208 (2024)
In the rapidly evolving landscape of smart transportation, the passenger volume in urban rail transit consistently demonstrates an upward trajectory. In this context, precise and scientifically grounded short-term passenger flow prediction methods ar
Externí odkaz:
https://doaj.org/article/192086ed6c1940c2914ec0cf7194a7bf
Publikováno v:
Mathematics, Vol 12, Iss 22, p 3556 (2024)
Accurate and timely passenger flow prediction is important for the successful deployment of rail transit intelligent operation. The Sparrow Search Algorithm (SSA) has been applied to the parameter optimization of a Long-Short-Term Memory (LSTM) model
Externí odkaz:
https://doaj.org/article/3ca06f40995d41dabdf3cec636049508
Publikováno v:
Mathematics, Vol 12, Iss 20, p 3204 (2024)
Short-term origin–destination (OD) passenger flow forecasting is crucial for urban rail transit enterprises aiming to optimise transportation products and increase operating income. As there are large-scale OD pairs in an urban rail transit system,
Externí odkaz:
https://doaj.org/article/ebfd30b7ae774af38a505240656b6135
Publikováno v:
Urban Rail Transit, Vol 9, Iss 4, Pp 323-351 (2023)
Abstract Short-term passenger flow prediction (STPFP) helps ease traffic congestion and optimize the allocation of rail transit resources. However, the nonlinear and nonstationary nature of passenger flow time series challenges STPFP. To address this
Externí odkaz:
https://doaj.org/article/5bad901977d74f1a87b08d6d3b938fc2
Publikováno v:
Applied Sciences, Vol 14, Iss 18, p 8121 (2024)
Efficient operation of urban metro systems depends on accurate passenger flow predictions, a task complicated by intricate spatiotemporal correlations. This paper introduces a novel spatiotemporal graph neural network (STGNN) designed explicitly for
Externí odkaz:
https://doaj.org/article/89dae42befd541d38b73c8e325760606
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, we study the big data multi-strategy predator algorithm for tourist flow prediction and explore the application of the algorithm in optimizing the tourist flow prediction model to improve the prediction accuracy and efficiency. An adve
Externí odkaz:
https://doaj.org/article/8a07cb0a6fa14ba99a8b1c86db55e46d
Publikováno v:
IET Intelligent Transport Systems, Vol 17, Iss 4, Pp 767-779 (2023)
Abstract To explore the relevance between bus stops and make the real‐time prediction of bus passenger flow more accurate, this paper proposes a Traffic Forecast Model based on the Attention mechanism (TFMA). The model combines data preprocessing w
Externí odkaz:
https://doaj.org/article/4ddb83589cb34c7ea567baad5734e458