Container port throughput analysis and active management using control theory

Ngoc, Cuong Truong; Xu, Xiao; Kim, Hwan–Seong; Nguyễn, Duy Anh; You, Sam–Sang

doi:10.1177/14750902211020875

Cited by 5 publications

(4 citation statements)

References 28 publications

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“…They optimize the port operation through the theory of sliding membrane control. The test verifies the effectiveness of this method [9].…”

Section: Related Workmentioning

confidence: 53%

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Simulation Method of Port Petrochemical Industry Throughput Development under the Background of Integration of Port, Industry and City

Zhou¹,

Chen²

2023

IJACSA

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In order to accurately predict the changes in the throughput of port petrochemical products and facilitate the formulation of relative decisions, this paper analyzes the factors affecting the throughput of port petrochemical products in a city through the GRA method. After sorting and selection, PCA method is used for pretreatment. In the SVM algorithm, ICSO is used to obtain the best parameters and improve the prediction accuracy and efficiency. In view of the variability of future development, three development scenarios are set up to prepare for the throughput forecast of petrochemical products in a city's port. The results show that the optimization speed of ICSO algorithm is very fast. When the training iteration is 20, the best fitness value is obtained, which is 0.0572. The training effect of ICSO-SVM algorithm is good, the gap between it and the original data is small, and the overall trend is close to the original data. In the test prediction, ICSO-SVM algorithm has the best prediction effect, and its MAE, RMSE and MAPE are the smallest. The minimum MAE is 762.2, 477.0 smaller than CSO-SVM algorithm, and the latter's MAE is 1239.2. The minimum MAPE of the proposed algorithm is 1.05%, while that of CSO-SVM algorithm is 1.71%. In general, the prediction error of ICSO-SVM algorithm is smaller. After the prediction of different development scenarios, the throughput of petrochemical products in a port of a city shows an increasing trend in the next five years. This method can be applied to the development forecast of port petrochemical products and provide reference for decision-making.

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“…They optimize the port operation through the theory of sliding membrane control. The test verifies the effectiveness of this method [9].…”

Section: Related Workmentioning

confidence: 53%

“…This variable can be generated by a specific chaotic map, and its initial population distribution range is much larger than the random variable, and can be combined with intelligent optimization methods. Among them, tent mapping is a typical method of generating chaotic sequence similar to tent, and the formula involved is shown in formula (9).…”

mentioning

confidence: 99%

Simulation Method of Port Petrochemical Industry Throughput Development under the Background of Integration of Port, Industry and City

Zhou¹,

Chen²

2023

IJACSA

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“…In particular, in a port supply chain, more resilient management should be adopted to address the risks posed by natural disasters. The two types of supply chain risks were defined as "parametric perturbations" and "external disturbances" [25]. Prominent methods include Bayesian networks, fuzzy logic theory, event tree analysis (ETA), fault tree analysis (FTA), multi-criteria decision analysis (MCDM), etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Port Risk Assessment Based on Various Meteorological Disasters

Wang,

Ding,

Poo

et al. 2024

Urban Science

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Within the framework of economic globalisation, ports serve as critical junctures in international trade and play a vital role. However, as infrastructure is closely linked to the natural environment, ports are highly susceptible to the impacts of meteorological disasters. Therefore, a comprehensive assessment of the risks posed by meteorological hazards to ports, establishing corresponding early warning mechanisms, and adopting reasonable response and recovery strategies, is paramount in ensuring the safe operation of ports and maintaining the stability of international trade. This study has comprehensively analysed historical data and identified the pre-established loss stratification system, improving the theoretical construct of “expected loss”. Additionally, this research has innovatively integrated the idea of preventative factors aligned with risk indicators. A quantitative algorithm was used to factor in the preventative factors within the computational procedure, deriving the weights pertinent to each risk indicator. This research aimed to reduce the subjectivity inherent in the weighting assignment process through such an approach, thereby enhancing disaster risk assessment’s scientific rigour and reliability. Moreover, it underscores the critical role of adaptive urban planning in enhancing the resilience of crucial economic nodes like ports, thereby contributing to the broader objectives of sustainable urban development.

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“…Trade globalization has promoted the vigorous development of the shipping industry, but followed by the problem of waterway and port dredging. [1][2][3][4] Cutter suction dredger is a kind of dredger widely used in dredging engineering, which has the advantages of high construction efficiency and low comprehensive cost. 5,6 With the increase of equipment excavation capacity and haul distance, it is more widely used in dredging and hydraulic reclamation construction.…”

Section: Introductionmentioning

confidence: 99%

Productivity regression analysis of cutter suction dredger considering operating characteristics and equipment status

Shang

Tian³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part M:

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In order to optimize the operation parameters of cutter suction dredger in real time and adjust productivity as needed, a construction optimization strategy based on real-time productivity regression analysis is proposed. Machine learning methods, including Support Vector Regression (SVR), Gradient Boosting Regression Tree (GBRT), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and a Super Learner that made up of them, are used to mine relevant features based on the big data of operation characteristics and equipment status. Firstly, the working principle of cutter suction dredger is analyzed, the features that need real-time monitoring are determined, and the above features are classified. Then, some missing values and outliers in the data are deleted. Next, Lasso method is used to eliminate the variables that are not related to the regression target, and the redundant variables are combined. In addition, five machine learning methods are used to train and test the off-line productivity data of cutter suction dredger. And they are used to fit recent online productivity data. Super Learner performed best, which achieved the highest R2 (0.917), the lowest RMSE (75.096) and MAE (61.422) in the five models for online regression. Furthermore, the calculation time of each model is discussed, and the feasibility of the method proposed in this study for real-time regression of online productivity data has been confirmed. Finally, the importance of characteristics is analyzed to provide guidance for dredging operations under restricted construction conditions. According to the regression results and the importance of features, operators can give priority to adjusting some features to adjust the real-time construction productivity of dredger.

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Container port throughput analysis and active management using control theory

Cited by 5 publications

References 28 publications

Simulation Method of Port Petrochemical Industry Throughput Development under the Background of Integration of Port, Industry and City

Simulation Method of Port Petrochemical Industry Throughput Development under the Background of Integration of Port, Industry and City

Research on Port Risk Assessment Based on Various Meteorological Disasters

Productivity regression analysis of cutter suction dredger considering operating characteristics and equipment status

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