Port Cargo Throughput Research Articles

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Purpose Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.Design/methodology/approach Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.Findings In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.Practical implications The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.Originality/value Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

Optimizing Port Multi-AGV Trajectory Planning through Priority Coordination: Enhancing Efficiency and Safety

Efficient logistics and transport at the port heavily relies on efficient AGV scheduling and planning for container transshipment. This paper presents a comprehensive approach to address the challenges in AGV path planning and coordination within the domain of intelligent transportation systems. We propose an enhanced graph search method for constructing the global path of a single AGV that mitigates the issues associated with paths closely aligned with obstacle corner points. Moreover, a centralized global planning module is developed to facilitate planning and scheduling. Each individual AGV establishes real-time communication with the upper layers to accurately determine its position at complex intersections. By computing its priority sequence within a coordination circle, the AGV effectively treats the high-priority trajectories of other vehicles as dynamic obstacles for its local trajectory planning. The feasibility of trajectory information is ensured by solving the online real-time Optimal Control Problem (OCP). In the trajectory planning process for a single AGV, we incorporate a linear programming-based obstacle avoidance strategy. This strategy transforms the obstacle avoidance optimization problem into trajectory planning constraints using Karush-Kuhn-Tucker (KKT) conditions. Consequently, seamless and secure AGV movement within the port environment is guaranteed. The global planning module encompasses a global regulatory mechanism that provides each AGV with an initial feasible path. This approach not only facilitates complexity decomposition for large-scale problems, but also maintains path feasibility through continuous real-time communication with the upper layers during AGV travel. A key advantage of our progressive solution lies in its flexibility and scalability. This approach readily accommodates extensions based on the original problem and allows adjustments in the overall problem size in response to varying port cargo throughput, all without requiring a complete system overhaul.

An empirical study on the economic linkage characteristics of Yangtze River port cities based on discrete second-order derivatives

Abstract Rapid economic development cannot be achieved without a well-developed trade in goods of various forms, so it depends on the construction and development of coastal or inland ports. How to coordinate the relationship between ports and cities in the development process is of great significance to the sustainable development of port cities, and is also an important part of the current research on ports. This paper uses gray correlation model to study the correlation between city economic development indexes and port development indexes, and finds that the correlation between GDP and gross industrial output value and port cargo throughput is the largest, and on the basis of gray correlation analysis, the impulse response analysis finds that the growth of total economic volume and gross industrial output value of port cities has an obvious promotion effect on the development of ports in the short term. The research results show that the value added of Nanjing’s tertiary industry drives the port logistics of Nanjing port most significantly; the growth rate stabilizes at 0.006 after the 11th period. The growth of Nanjing port container throughput on the value added of Nanjing’s secondary industry changes most significantly and finally stabilizes at 0.0035.

Evaluation and obstacle factors of marine resources and environment carrying capacity in Beibu Gulf Urban Agglomeration

With the strong support of the Chinese government, the Beibu Gulf Urban Agglomeration has responded positively to the national call to vigorously develop the marine economy. However, a series of marine resource and environmental problems such as over-exploitation of marine resources and excessive discharge of marine pollutants in the Beibu Gulf Urban Agglomeration has also arisen along with the rapid development of the marine economy, limiting the space for the development of the marine economy in the Beibu Gulf Urban Agglomeration. Based on the panel data of seven coastal cities in the Beibu Gulf urban agglomeration from 2011-2021, the DPSIR model was used to construct a marine resources environmental carrying capacity evaluation index system including five dimensions of driving force, pressure, state, impact and response, and the TOPSIS model with combined weighting was used to make a comprehensive evaluation of the marine resources carrying capacity of the Beibu Gulf urban agglomeration, and then the barrier degree model was used to explore the barriers to the carrying capacity of marine resources and environment in the Beibu Gulf Urban Agglomeration. The empirical results show that, on the whole, the marine resources and environment carrying capacity of the seven coastal cities in the Beibu Gulf Urban Agglomeration show an upward trend. From the situation of each subsystem, the pressure subsystem and response subsystem have greater evaluation values, while the evaluation of the driving force, state, and influence subsystem needs to be improved; from the analysis of obstacle factors, the main single indicator obstacle factors include per capita coastline length, total import and export volume, and port cargo throughput, etc. The status subsystem is the main classification indicator barrier factor affecting the improvement of the marine resource and environmental carrying capacity of the Beibu Gulf Urban Agglomeration. Based on the results of the empirical analysis, corresponding suggestions are put forward.

Port container throughput prediction method based on SSA-SVM

To improve the prediction accuracy of the port cargo throughput and the applicability of the prediction model, and then provide data support for the port construction to meet the needs of port decision-making, take the monthly cargo throughput data of Shanghai Port from January 2009 to December 2022 as an example, use Pearson correlation analysis to screen 12 import and export impact factors. This paper improves the traditional SVM model, uses SSA (Sparrow Search Algorithm) to optimize the parameters c and g in SVM, and uses the model to predict. Compared with the model that uses the grid search algorithm to optimize the parameters of SVM, the model has a significant improvement in fitting and robustness, its predicted value is closer to the actual value, the prediction performance is better, and it can better reflect the actual state of the port.

The Relationship between Port and City Growth: The Case of Ningbo

Purpose – The purpose of this paper is to explore the relationship between port and city growth with the help of the port impact curve and relative concentration index (RCI). This is done from the two aspects of (1) clarifying the characteristics of the interaction between Ningbo port and city, and (2) clarifying the phased development of the relationship between Ningbo port and city. Design/Methodology/Approach – Based on the method of the port impact curve and RCI, we conduct a case study of Ningbo, a port-city in Southeast China, and we also make a meaningful comparison between Ningbo and other famous port cities in China. Findings – This paper finds that Ningbo port and city have been in a relatively loose relationship from 2010 to 2021. Over these 12 years, the relationship between Ningbo port and city has shown signs of changing from the stage of agglomeration and diffusion effect to the stage of urban selfgrowth effect. Also, we find that, compared with other port cities, the positive correlation between Ningbo port cargo throughput and urban economy development is relatively weak. However, Ningbo’s export-oriented economic characteristics form a certain boost for the development of port container throughput. Research Implications – In the management of this paper, this study revealed the flexibility and complexity of the port-city relationship, suggesting that the stage characteristics of the port-city relationship should be combined on the road of the sustainable development of ports and cities, which will also provide reference for follow-up research.

Deep learning-based forecasting of port cargo throughput using PCA and error correction multivariate LSTM

Deep learning-based forecasting of port cargo throughput using PCA and error correction multivariate LSTM

Regional Collaborative Forecast of Cargo Throughput in China's Circum-Bohai-Sea Region Based on LSTM Model.

Any developed port plays a dominant role both in domestic and international trade reflecting economic prosperity of the port and nearby regions in terms of its cargo throughput and port construction. An attempt is made in this study to use long-and short-term memory (LSTM) artificial neural network method to construct the port cargo throughput prediction model. Three ports namely, Tianjin Port, Dalian Port, and Tangshan Port from China's Bohai Rim region are selected as research objects. The historical cargo throughput of each port for nearly ten years was used as the input index data for joint prediction. The cargo throughput of Bohai Port provides another way to improve the accuracy of port cargo throughput prediction. The prediction results show that the LSTM model can effectively predict the port cargo throughput; the cargo throughput forecasts between the three Bohai Rim ports have both an interactive relationship and differences.

Research on the Construction of Comprehensive Evaluation Index System of Influencing Factors of Port Industry Based on Data Analysis

In this paper, 12 indicators are selected from five categories of factors affecting the port industry: port infrastructure conditions, port operation and service capacity, port hinterland economic conditions, upstream development status of the industry chain and port development potential. The port cargo throughput, berth, port and berth for production quantity, the total length of the port city GDP, the second industry output port city, port city of the tertiary industry output value, port city GDP growth, investment in fixed assets, the balance of loans of financial institutions, total import and export of foreign trade port city, port city actually realized foreign investment total income of postal and telecommunication services, port city, through the analysis of these data to build a set of unique and complete factors comprehensive evaluation index system of port industry.

Algorithm Design of Port Cargo Throughput Forecast Based on the ES‐Markov Model

At present, the existing prediction algorithm of a port cargo throughput neglects the correction of the initial value of the cargo series data model, which leads to a large error in a port cargo throughput prediction. Therefore, a prediction algorithm of a port cargo throughput based on the ES‐Markov model is designed. A decompose function is used to decompose the time series of a port cargo throughput, and the trend elements of a port cargo throughput are divided into long‐term trend, seasonal trend, fluctuation trend, and irregular trend. In this study, the ES‐Markov model is introduced, and the initial prediction is obtained by using the cubic exponential smoothing method, and the state transition matrix is obtained by the Markov principle. Based on the results of the time‐series analysis and the ES‐Markov model, the prediction algorithm of a port cargo throughput is designed. In the experimental design, the Elman neural network is used to construct an experimental sample data model. The monthly cargo throughput data of a certain port for eight months from May 2020 to December 2020 are collected and sorted according to the time series. The experimental results show that the prediction results of the proposed algorithm are closer to the actual value and the fluctuation of the prediction results is less than that of the reference.

Prediction Study of Tianjin Port Throughput Based on GM (1, 1) Extended Model

Tianjin Port is the largest comprehensive main hub port and one of the main transshipment ports for energy and raw materials transportation in northern China. It has freight business with many countries. At the same time, Tianjin Port is the first port to carry out international maritime container transportation in China’s coastal areas. Tianjin Port was built in the 1950s, and the container business has been started since 1973, In recent years, with the rapid development of large-scale, intensive and intelligent container ships in Tianjin Port, cargo throughput is an important indicator in the comprehensive evaluation of port development, which represents the development level of a port. At the same time, it also brings new tasks to the navigation guarantee work, in particular, it puts forward systematic requirements for port and wharf construction, navigation aids layout, navigation aids efficiency display and navigation aids base layout. The annual throughput of port cargo or container is one of the bases of world ports. As an output index, port enterprises, shipping companies, navigation guarantee departments and shipping economic analysis departments attach great importance to it. Therefore, the prediction of Tianjin Port cargo throughput can provide reference for Tianjin Port’s next development planning, waterway use and navigation guarantee planning and layout, navigation aids setting, wharf construction, route mapping, etc. the article constructs of Tianjin Port. The average error is 0.29%, and the prediction accuracy is first class. This model can better predict the change trend of cargo for Tianjin Port, which is a better way to analyze the change trend for Tianjin port.

Research on Shanghai Port Logistics Based on VAR Model

This article mainly analyzes how to use the vector autoregressive VAR model to study the development of Shanghai port logistics. First, the use of co-integration test to analyze the long-term co-integration relationship between Shanghai port logistics and the regional economy; Then, by constructing a vector autoregressive model of port cargo throughput and Shanghai’s GDP, construct an impulse response function to analyze the dynamic mechanism between the two; Then analyze the contribution rate between the two through variance decomposition.

Forecasting the Logistics Demand of Guangxi Beibu Gulf Port

Objective - The objective of this paper is to establish the forecasting models of port cargo throughput and container throughput in Guangxi Beibu Gulf Port in the next 5 years, and to put forward the countermeasures of port logistics development in Guangxi Beibu Gulf Port according to the forecast results. Methodology/Technique – The data of cargo throughput and container throughput of Guangxi Beibu Gulf Port and 3 port areas of Beihai, Fangcheng and Qinzhou in 2009-2020 are collected through the data of Guangxi Statistical Yearbook and Guangxi Statistical Bulletin. Based on 2019 and 2020, the forecasting models of cargo throughput and container throughput in Guangxi Beibu Gulf Port and 3 port areas of Beihai, Fangcheng and Qinzhou are establishe using a weighted moving average forecasting method. The cargo throughput and container throughput of Guangxi Beibu Gulf Port and 3 port areas of Beihai, Fangcheng and Qinzhou in 2020/2021-2025 are predicted. Findings – The forecast results show that by 2025, the cargo throughput of Guangxi Beibu Gulf Port is expected to exceed 400 million tons, and the container throughput is expected to exceed 10 million TEU. According to the fitting diagram of forecast results and actual data, it can be seen that the accuracy of the forecast results is very high. Novelty – It is innovative to select 2 base years in 2019 and 2020 to establish forecasting model. Based on the comparative analysis of the forecast results, this paper puts forward various measures to promote the development of port logistics of Guangxi Beibu Gulf port, such as strengthening the construction of port self-condition, strengthening the co-ordinated development of port and economic hinterland, speeding up the construction of port collection and distribution system, training and introducing all kinds of high-quality port logistics talents. Type of Paper: Empirical. JEL Classification: C53, R41. Keywords: Logistics Demand Forecast; Cargo Throughput Forecast; Container Throughput Forecast; Weighted Moving Average Forecasting Method; Guangxi Beibu Gulf Port Reference to this paper should be made as follows: Yue, N. (2021). Forecasting the Logistics Demand of Guangxi Beibu Gulf Port, GATR Global J. Bus. Soc. Sci. Review, 9(1): 73 – 89. https://doi.org/10.35609/gjbssr.2021.9.1(9)

Impact of COVID-19 Lockdown on Air Pollutants in a Coastal Area of the Yangtze River Delta, China, Measured by a Low-Cost Sensor Package

Ningbo is a major coastal city in the Yangtze River Delta region, China, with the largest cargo capacity in the world. We conducted a field campaign in Ningbo to measure the impact of the COVID-19 lockdown on air pollutants including NO2, O3 and CO from 21 January to 23 March 2020, using a home-made low-cost sensor package. The average concentrations of NO2, O3 and CO were observed to be 7.2, 37.5 and 648.5 ppb, respectively, during the lockdown. Compared with the previous year, the concentrations of NO2 and CO decreased by 63.1% and 6.9%, while the concentration of O3 increased by 37.9%. The significant reduction of NO2 concentration may be attributed to the reduced emissions of freighters and heavy trucks with lower port cargo throughput, which led to a decrease of NO concentration. The increase of O3 concentration was probably due to the lower titration of O3 by NO. After the lockdown, the concentrations of O3 and NO2 increased by 15.5% and 143.1%, respectively, compared with those during the lockdown. The temporal variations of the concentrations of NO2, O3 and CO measured by the sensor package were coincident with those obtained by the reference apparatus, which proves the sensor package to be suitable for air quality monitoring in field campaigns. This is the first time that a dramatic decrease in NO2 concentration in a coastal city due to a lockdown has been reported.

The Arctic policy and port development along the Northern Sea Route: Evidence from Russia's Arctic strategy

As global warming continues, the melting rate of Arctic glaciers is further accelerated, which provides favorable conditions for the development of the Arctic's abundant resources, shipping, and ecological research. Accordingly, Russia, as the country with the longest Arctic coastline, has promulgated a series of policies and guidelines which aimed at the development of the Arctic region and the revitalization of the Northern Sea Route (NSR). By strengthening infrastructure construction, reducing port dues, and improving handling efficiency to promote the development of ports along theNSR and also to gives full play to the transportation potential of NSR, which is an inherent need for the development of Russian Arctic region. However, how Russia's Arctic strategy may affect port development along the NSR and whether the Russian arctic strategy can promote the development of ports along the NSR remain to be investigated. This study, based on the multi-source data, uses the difference-in-difference (DID) method to estimate the impact of Russia's Arctic strategy on the development of ports along the NSR. The results from this study indicate that Russia's Arctic strategy has failed to promote the development of ports along the NSR during 2003–2012, and the growth of port cargo throughput is overly reliant on energy exploitation. All of our preliminary results throw light on the nature of the impact of Russia's Arctic strategy on the development of ports along the NSR.

Research on Port Infrastructure, Port Efficiency and Urban Trade Development

Liu, M.L., 2020. Research on port infrastructure, port efficiency and urban trade development. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 220-222. Coconut Creek (Florida), ISSN 0749-0208.With the progress of science and technology and the continuous development of productivity, economic globalization and regional economic grouping have become irreversible trends. Interactive development of port infrastructure and port city economy is an important guarantee for sustainable and rapid development of regional economy. The improvement of port infrastructure such as port cargo throughput, number of berths and terminal length can promote trade development. Port efficiency is specific in today's global trade. If we think that port efficiency is not specific in global trade, or if we do not have a far-sighted prediction of global trade, we cannot see the long term after all. With the development of port economy, the competition of port logistics has changed from cost difference to service difference. This paper explores the relationship between foreign trade and the level of port infrastructure and port efficiency in China's coastal cities, trying to find out the factors that have been ignored by all sectors in the past but have an important role in the development of trade.

A Grey Theory-Based Economic Prediction Method of Port and Ocean Engineering

Liu, J., 2020. A grey theory-based economic prediction method of port and ocean engineering. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 197–200. Coconut Creek (Florida), ISSN 0749-0208.With the rapid development of science and technology, economic prediction has been applied to many fields of economic events, mainly to predict the development of law and future situations. Through scientific prediction, we can provide a rigorous scientific basis for economic activities. There are a variety of prediction methods and theories, such as grey theory, fuzzy prediction method, time series method, compound interest method, etc. With the rapid growth of China's economy, China's port and marine engineering has made great achievements and has become an indispensable economic growth point in China's national economy. Therefore, on the basis of the grey theory, this paper makes a grey model first-order one variable (GM [1,1]) model prediction of port and marine engineering economy, which mainly includes three aspects: gross ocean product, port cargo throughput, and container throughput in coastal areas. Through the GM (1,1) model, we can correctly understand and predict the throughput of the port. Finally, this paper puts forward some suggestions that can better carry out the economic development of port and marine engineering.

Optimization of Marine Port Logistics Collection and Distribution Network: A Perspective of Supply Chain Management

Yang, J. and Guo, L., 2020. Optimization of marine port logistics collection and distribution network: A perspective of supply chain management. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 473–476. Coconut Creek (Florida), ISSN 0749-0208.With the prosperity of financial trade, marine port logistics have become an important part of international logistics, which needs to improve port efficiency by optimizing the collection and distribution network. A collection and distribution network is a kind of system that integrates multiple transportation modes, including railway, highway, waterway, air transport, pipeline, etc. Zhoushan Port in Ningbo is the largest port in China. With the gradual increase in the importance of marine port logistics, the original collection and distribution network has been unable to meet the rapid growth of port cargo throughput. Therefore, the marine port's collection and distribution network system needs to be optimized based on the supply chain. This paper presents an analysis of the optimization of Zhoushan Port's collection and distribution network based on the supply chain. First, this paper forecasts the cargo throughput and container throughput of Zhoushan Port using the Grey method. Then, this paper predicts the capacity of different transportation networks. Finally, some suggestions are put forward.

Forecasting of Port Cargo Throughput Based onElman Neural Network

Forecasting of Port Cargo Throughput Based onElman Neural Network

The Relationship between Port Logistics and International Trade Based on VAR Model

Wu, J., 2020. The relationship between port logistics and international trade based on VAR model. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 601–604. Coconut Creek (Florida), ISSN 0749-0208.This paper puts forward the analysis method of port logistics and international trade based on VAR model. Based on the collection of information resources related to port logistics and foreign trade, the empirical analysis of the relationship between port logistics and international trade is carried out according to the collection results, combined with the grey correlation theory and VAR model. This work analyze the correlation between international trade and port logistics by using grey correlation degree, builds the corresponding VAR model, and analyzes the relationship between the two. It was found that there is and stable equilibrium relationship among trade, port cargo throughput and container throughput. Finally, the paper gives some suggestions on the development of port logistics and international trade from the aspects of strengthening regional cooperation of port logistics, strengthening government work, strengthening industry cooperation and strengthening personnel training of enterprises.