Cascading Failure in Multiple Critical Infrastructure Interdependent Networks of Syncretic Railway System

In order to improve the prediction accuracy of train passenger load factor of high-speed railway and meet the demand of different levels of passenger load factor prediction and analysis, the influence factor of the train passenger load factor is analyzed in depth. Taking into account the weather factor, train attribute, and passenger flow time sequence, this paper proposed a forecasting method of train passenger load factor of high-speed railway based on LightGBM algorithm of machine learning. Considering the difference of the influence factor of the passenger load factor of a single train and group trains, a single train passenger load factor prediction model based on the weather factor and passenger flow time sequence and a group of trains’ passenger load factor prediction model based on the weather factor, the train attribute, and passenger flow time sequence factor were constructed, respectively. Taking the train passenger load factor data of high-speed railway in a certain area as an example, the feasibility and effectiveness of the proposed method were verified and compared. It is verified that LightGBM algorithm of machine learning proposed in this paper has higher prediction accuracy than the traditional models, and its scientific and accurate prediction can provide an important reference for the calculation of passenger ticket revenue, operation benefit analysis, etc.

Section: Influence Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction and Analysis of Train Passenger Load Factor of High-Speed Railway Based on LightGBM Algorithm

Wang

Chen

et al. 2021

“…In the path optimization of multimodal transport, many scholars have made in-depth research based on different aspects. Fazayeli et al [9] studied the problem of multimodal transport path optimization under fuzzy demand, established a mixed-integer fuzzy mathematical model, and solved it by genetic algorithms [10]; Fotuhi studied the optimization problem of multimodal transport path with uncertain network topology [11]; Idri et al [12] introduced a search method for the shortest path algorithm in parallel distributed architecture to solve the path optimization problem of dynamic multimodal transport network with time dependence [13,14]; Liu et al [15] established a super transportation network to predict the generalized cost of multimodal transportation, which provides technical support for the comprehensive transportation planning. Li constructed a route selection model for cargo multimodal transportation and used an improved ant colony algorithm to be solved.…”

Section: Introductionmentioning

confidence: 99%

“…At present, the research on multimodal transport does not consider the influence of natural factors such as weather, terrain, and some special human factors on the transport [15]. In actual transportation, these factors may lead to the delay [27] of transport time, and even the occurrence of dangerous accidents [28] and damage of goods.…”

Section: Introductionmentioning

confidence: 99%

Route Selection of Multimodal Transport Based on China Railway Transportation

Zhang

et al. 2021

Self Cite

The advantage of multimodal transport is that it can deliver the goods to their destination in a reasonable combination of transport modes while ensuring security and punctuality. Multimodal transportation can effectively reduce logistics costs, improve logistics efficiency, and reduce environmental pollution. In the process of multimodal transportation, due to the interference of natural factors (weather, terrain, etc.) and some special human factors, it may have different degrees of impact on the transportation time and transportation safety of different transportation modes. Therefore, when choosing a transportation method, it is necessary to consider the transportation time and transportation safety under the interference. However, the current research on multimodal transport has not considered the impact of external interference on transportation time and transportation safety. Compared with other modes of transportation, external interference has a relatively small impact on railway transportation. Railways can safely deliver goods to their destinations on time. Under the background of China’s huge railway network and advanced heavy-duty technology, this paper establishes a multimodal transport route selection model for considering railway as the core, introduces time penalty cost and damage compensation cost, and takes the lowest comprehensive transportation cost as the model objective under the premise of considering transportation reliability and transportation safety. Finally, taking a multimodal transport network in China as an example, an improved ant colony algorithm is used to solve the model and the results verify the rationality of the model.

“…ere are many differences in the information system construction architecture of various ports, which lead to serious information heterogeneity. At the same time, this information processing mode requires the railway to dock with different ports one by one, which will consume a lot of unnecessary time when the railway information is docked with the port business process, and the port also lacks effective expectation and control of the business growth [2]. With the continuous emergence of new combined transport services and the rapid expansion of the scale of services, the entropy value of the combined transport information system scattered in various ports will increase rapidly and cannot bear the burden of business development [3].…”

Section: Introductionmentioning

confidence: 99%

The Business Process Reconstruction of Railway-River Combined Transportation Cloud Platform Taking China Container Export as an Example

Jia

Sun

Yuan

et al. 2021

In recent years, major large ports in China have realized the business informatization of rail-water intermodal transportation. However, the overall development level of intermodal transportation informatization has been restricted to a great extent due to the unbalanced development of intermodal transportation informatization in different regions, the rigid system architecture, the low degree of information sharing, and the lack of data management and analysis methods. Combined with the structure and business characteristics of intermodal transportation information systems, adopting cloud computing and Big Data technology, we propose an intermodal transportation information process with waybill as the information carrier and FPMS as the service fulcrum in this paper. Illustrated by the example of China’s container export process, this paper explores a series of key technical issues in the cloud environment, such as application management, business information sharing, and Big Data processing, at different levels of the construction of the rail water transport cloud platform, combined with its business characteristics, and makes experimental analysis on the relevant models to verify the feasibility of the reconstruction of the rail water transport cloud platform. It can provide theoretical and practical support for the development of rail water intermodal informatization in China.