Mathematical Modeling of Multimodal Transportation Risks

Ніценко, Віталій; Kotenko, Sergiy; Hanzhurenko, Iryna; Mardani, Abbas; Stashkevych, Ihor; Karakai, Maksym

doi:10.1007/978-3-030-36056-6_41

Cited by 50 publications

(47 citation statements)

References 7 publications

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“…In the work [12], the problem of multimodal (combined) transportation of cargoes is proposed to be considered by means of the construction of an appropriate digraph. The factor of uncertainty and fuzzy variables complicates the implementation of the method described in [12].…”

Section: Methodsmentioning

confidence: 99%

“…Uncertainty leads to the need to generalize the method described in [12], using the recommendations given in [14], [15] applying intuitionistic dominant half-variants (IDNs), unlike fuzzy sets, IDNs are characterized to some extent by independence of degrees of membership and non-membership.…”

Section: Methodsmentioning

confidence: 99%

“…The use of the apparatus of correlation-regression analysis in the case of multimetric regression (and the factors of CT, characterized by the presence of uncertainty, as the study showed, are multimetric) is complicated by the multicollinearity of the parameters. For cases where the mathematical apparatus of regression-correlation analysis cannot be used, it is suggested to use the mathematical apparatus of fuzzy sets, if necessary, combining them according to the algorithm [12].…”

Section: Fig 1 -Flowchart Of Algorithm Implements a Universal Mathemmentioning

confidence: 99%

“…Using graph theory methods to formulate a route, this will be realised on a digraph by the algorithm of selecting nodes closest to the current one which are connected with the terminal route by intermediate edges and nodes with no signs of uncertainty. Then the problem is reduced to the method described in [12] for finding the optimal path by selecting more efficient nodes (edges, stages of transportation) on the digraph.…”

Section: Fig 1 -Flowchart Of Algorithm Implements a Universal Mathemmentioning

confidence: 99%

“…Different approaches are used for mathematical modeling of transport systems, including the use of graph theory [7], [8], [9], [10], [11]. In our view, the approach to mathematical modeling of combined (multimodal) transportations described in the work [12] is more appropriate.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation

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Tongkaw

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This research aims to study the relationship between parallel processing efficiency and several nodes on a single board cluster using a mathematical model, approximating least squares. This research tested on the Raspberry Pi single-board in the form of a high-performance computing system. It divided the tasks that need to be processed in each particular part and sent it to each unit to process simultaneously via the MPI (Messaging Passing Interface). This process is the standard division of work with communication between processors in the form of messages on the cluster system. It consists of eight nodes of Raspberry Pi. It measures the instruction set's ability to perform decimal operations per second or Floating-point Operation Per Second (FLOPS) with High-Performance Linpack Benchmarks (HPL). As a result, the efficiency of the ability to process instruction set in decimal per second increases the performance continuously when increasing the number of the node on the cluster. Which corresponds to the mathematical model obtained f(x) = 1.0684x^(0.8256).It shows a relationship between parallel processing performance values and the number of nodes on the cluster and can be estimated with the mathematical model above.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Fig 1 -Flowchart Of Algorithm Implements a Universal Mathemmentioning

confidence: 99%

Section: Fig 1 -Flowchart Of Algorithm Implements a Universal Mathemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation

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Risk assessment on multimodal transport network based on quality function deployment

Guo

et al. 2020

Int J Intell Syst

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As a necessary work before risk prevention and control, risk assessment has become increasingly important in multimodal transport networks. On the basis of the idea of quality function deployment (QFD), this paper combines fuzzy G1 method, two-tuple linguistic representation model, and dynamic intuitionistic fuzzy multi-attribute evaluation method to propose a new method for risk assessment. QFD is innovatively used to create an overall framework, which includes the basic importance rating of risk factors, the correlation between risk factors and network failures, the importance rating of network failures, and the comprehensive importance rating of risk factors. The comprehensive importance rating is regarded as an indicator to verify, improve, and modify the basic importance rating, which can make up for the disadvantage of the existing risk assessment methods in proving the credibility of the results. Its result is the key to judging the degree of influence of risk factors on network operation. This paper takes the multimodal transport network in the Sichuan-Tibet region of China as an example for analysis. The results are analyzed and discussed to prove the validity and advancement of the proposed method.

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Societal Content and Main Determinants of “National Security” Phenomenon in the Information and Communication Context

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Mathematical Modeling of Multimodal Transportation Risks

Cited by 50 publications

References 7 publications

Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation

Mathematical Model for Approximation the Efficiency of Parallel Computing on Single Board Cluster with Least-squares Approximation

Risk assessment on multimodal transport network based on quality function deployment

Societal Content and Main Determinants of “National Security” Phenomenon in the Information and Communication Context

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