Discrete Event-Based Railway Simulation Model for Eco-Efficiency Evaluation

Amorim, G. A.; Lopes, Luiz Antônio Silveira; Silva, O. S.

doi:10.2507/ijsimm19-3-517

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…(2) For the obtained candidate distance sequence, calculate the corresponding soft distance for kind class j according to equation (3).…”

Section: Convergence Experimentmentioning

confidence: 99%

“…Rough set theory [1] is concerned with vagueness and granularity in terms of approximations [2]. To date, the theory has been applied in many research fields, including knowledge discovery, pattern recognition, information processing, granular computing, and data analysis [3][4][5][6][7]. In recent years, many researchers have established generalized rough set models, e.g., rough fuzzy set and fuzzy rough set models, neighborhood rough sets, probabilistic rough sets, rough sets for decision theory, soft rough sets, and general binary relations [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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Modelling Enterprise’s Coordinated Development Strategy with a Soft Fuzzy Rough Set

Wang

Cui

2021

Discrete Dynamics in Nature and Society

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With the concept of sustainable development, enterprises are facing severe challenges in ecological protection and economic development. Approaches to improving effectiveness of the coordinated development strategy must continue to evolve to address uncertainty and hazards that may be encountered in the future. We propose a coordinated development strategy model based on the combination of soft fuzzy and rough set theory and construct its prediction model. For the multistrategy dataset in the paper, parameter for each kind shall be selected through converting the multistrategy data into two prediction datasets. An algorithm transformed by SFRC shall be subject to weighted average for each parameter. Furthermore, we use training methods and soft fuzzy rough sets’ learning algorithm to calculate, and the evaluating indicator rough set is constructed with a three-tier model structure. After the final rough set training is completed, test results show that the rough set model which has a higher rating accuracy builds a better completed business performance evaluation. By comparing the prediction effect, both SVM algorithm and multistrategy prediction model for the soft fuzzy rough set in the paper can realize effective prediction for the enterprise’s coordinated development strategy. Moreover, the prediction result obtained at the time of adopting boundary to get the expected value is superior to that of giving one fixed threshold. It shows that the prediction performance of the algorithm in the paper is more excellent and represents the advantage of the algorithm prediction performance at the time of adopting boundary to get the expected value. The model provides support methods to assist enterprise management in making more efficient and scientific decisions for enterprise’s coordinated development.

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“…(2) For the obtained candidate distance sequence, calculate the corresponding soft distance for kind class j according to equation (3).…”

Section: Convergence Experimentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling Enterprise’s Coordinated Development Strategy with a Soft Fuzzy Rough Set

Wang

Cui

2021

Discrete Dynamics in Nature and Society

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“…Besides, it focuses on the analysis of the important progress of the coordinated development of Beijing-Tianjin-Hebei, starting from different aspects of coordination and clarifying the existence of industries, public services, transportation, ecology, and land use in the Beijing-Tianjin-Hebei region since the coordinated development. In combination with the current domestic and foreign environmental background of our country, the idea of coordinated development in the future is pointed out [6][7][8][9][10][11]. In addition to the separate study of the Beijing-Tianjin-Hebei region, some scholars have compared the Beijing-Tianjin-Hebei urban agglomeration with the Yangtze River Delta urban agglomeration and the Pearl River Delta urban agglomeration and found the coordinated development of the Beijing-Tianjin-Hebei region through horizontal comparisons [12][13][14][15][16].…”

Section: Literature Reviewmentioning

confidence: 99%

Coordinated Development of Regional Complex System: A Niche-Based Study

Fan

Bai

et al. 2021

Discrete Dynamics in Nature and Society

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Taking Beijing-Tianjin-Hebei as an example, it analyzes the comprehensive competitiveness of Beijing, Tianjin, and Hebei. It selects four dimensions: economic dimension, social dimension, environmental dimension, and technological dimension. From a new perspective, it explores the application of niche theory in regional synergy. Based on the analysis of the ecological niche, the coordination degree model of the composite system is further used to calculate the status quo of the coordinated development of the Beijing-Tianjin-Hebei region from 2013 to 2019. The results show that Beijing has the highest ecological niche, followed by Tianjin, and Hebei is the weakest. In 2019, the Beijing-Tianjin-Hebei region is at a good level of coordination, with the social subsystem having the highest order and the technological subsystem having the lowest order. Based on this, it is proposed that the Beijing-Tianjin-Hebei regions should be scientifically positioned, the overall need to be aligned with international trends, and the internal planning should be integrated to further enhance the level of cooperation in the Beijing-Tianjin-Hebei region.

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“…This technique allows the study of complex systems more quickly when compared to direct experimentation in real systems, which would consume enormous resources [2]. According to [3], DES creates, in a virtual environment, a representation of a real system to test different scenarios without risk and with low cost involved.…”

Section: Introductionmentioning

confidence: 99%

Facilitated Discrete Event Simulation for Industrial Processes: a Critical Analysis

Oliveira¹,

Leal²,

Pereira³

et al. 2022

Int. j. simul. model.

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Discrete Event Simulation (DES) is one of the most important simulation techniques in decision-making in several areas. Some authors state that small and large companies can benefit significantly through the utilisation of DES. Literature shows that most DES studies carried out are at large companies. Studies carried out at small and medium-sized enterprises (SMEs) have been mostly explored on a one-off, caseby-case basis, given the characteristics and limitations of smaller companies. In order to expand DES studies in a wide range of companies, this article seeks to consider the SME characteristics and limitations prevent them from broadly adopting traditional ("hard") DES. Then an alternative application of DES in "soft" mode was proposed. A review of facilitated DES frameworks was carried out. The frameworks were critically analysed in this review in relation to their adequacy to specific SME requirements and similar contexts. Finally, some issues and characteristics of these frameworks are presented that make directly applying in these contexts difficult. Furthermore, some suggestions are proposed for developing future facilitated DES frameworks.

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Discrete Event-Based Railway Simulation Model for Eco-Efficiency Evaluation

Cited by 8 publications

References 11 publications

Modelling Enterprise’s Coordinated Development Strategy with a Soft Fuzzy Rough Set

Modelling Enterprise’s Coordinated Development Strategy with a Soft Fuzzy Rough Set

Coordinated Development of Regional Complex System: A Niche-Based Study

Facilitated Discrete Event Simulation for Industrial Processes: a Critical Analysis

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