A new stepsize change technique for Adams methods

Calvo, M.; Montijano, J. I.; Rández, L.

doi:10.21042/amns.2016.2.00043

Cited by 9 publications

(5 citation statements)

References 13 publications

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“…In the present study, the strength of predictor-corrector Adams technique [22,23] and explicit Runge-Kutta numerical technique [24,25] is exploited to solve the second-order prediction differential model.…”

Section: Methodsmentioning

confidence: 99%

Design of a Novel Second-Order Prediction Differential Model Solved by Using Adams and Explicit Runge–Kutta Numerical Methods

Sabir

Guirao

Saeed

et al. 2020

Mathematical Problems in Engineering

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In this study, a novel second-order prediction differential model is designed, and numerical solutions of this novel model are presented using the integrated strength of the Adams and explicit Runge–Kutta schemes. The idea of the present study comes to the mind to see the importance of delay differential equations. For verification of the novel designed model, four different examples of the designed model are numerically solved by applying the Adams and explicit Runge–Kutta schemes. These obtained numerical results have been compared with the exact solutions of each example that indicate the performance and exactness of the designed model. Moreover, the results of the designed model have been presented numerically and graphically.

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Section: Methodsmentioning

confidence: 99%

Design of a Novel Second-Order Prediction Differential Model Solved by Using Adams and Explicit Runge–Kutta Numerical Methods

Sabir

Guirao

Saeed

et al. 2020

Mathematical Problems in Engineering

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“…This study artificially creates two economic information missing values, single mode missing and multi-mode missing. In single mode, each data object is allowed to contain only one missing value, while multipattern allows each data object to contain multiple missing values [21,22], and the missing values vary. The missing data are simulated by selecting 1%, 3%, 5% and 10% of the data from the data set and deleting some of the attribute values of the data.…”

Section: Experimental Process and Analysismentioning

confidence: 99%

Discretization Algorithm for Incomplete Economic Information in Rough Set Based on Big Data

Li¹,

Shen²

2020

Symmetry

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Discretization based on rough sets is used to divide the space formed by continuous attribute values with as few breakpoint sets as possible, while maintaining the original indistinguishable relationship of the decision system, so as to accurately classify and identify related information. In this study, a discretization algorithm for incomplete economic information in rough set based on big data is proposed. First, the algorithm for filling-in incomplete economic information based on deep learning is used to supplement the incomplete economic information. Then, based on breakpoint discrimination, the algorithm for discretization in the rough set is used to implement the discretization based on rough set for supplementary economic information. The performance of this algorithm was tested using multiple sets of data and compared with other algorithms. Experimental results show that this algorithm is effective for discretization based on a rough set of incomplete economic information. When the number of incomplete economic information rough candidate breakpoints increases, it still has a higher computational efficiency and can effectively improve the integrity of incomplete economic information, and finally the application performance is superior.

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“…More importantly, the scale, nature, and time of the tra c accident and tra c ow are uncontrollable variables. The duration of the tra c accident can be reduced by increasing the e ciency of the tra c accident response and handling [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34].…”

Section: Urban Road Tra C Flow Control Scheme Under Incidental Congesmentioning

confidence: 99%

Urban road traffic flow control under incidental congestion as a function of accident duration

2018

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An abrupt increase in urban road traffic flow caused by incidental congestion is considered. The residual traffic capacity varies in different lanes after an accident, and the influence of accident duration on traffic flow is taken into account. The swallowtail catastrophe model was built based on catastrophe theory. The critical state of traffic congestion under incidental congestion was analyzed using this model, and a traffic flow control scheme is proposed with the goal of maximizing the traffic capacity. Finally, the operational state of traffic flow under different scenarios is analyzed through case study and the feasibility of the model is validated.

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A new stepsize change technique for Adams methods

Cited by 9 publications

References 13 publications

Design of a Novel Second-Order Prediction Differential Model Solved by Using Adams and Explicit Runge–Kutta Numerical Methods

Design of a Novel Second-Order Prediction Differential Model Solved by Using Adams and Explicit Runge–Kutta Numerical Methods

Discretization Algorithm for Incomplete Economic Information in Rough Set Based on Big Data

Urban road traffic flow control under incidental congestion as a function of accident duration

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