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Intelligent analysis of import and export in green trade barrier based on big data analysis

Mao Yu, Lu Shan

Ecological Chemistry and Engineering. S

2024

Vol. 31, nr 1

117--126

With the rapid development of economic globalisation, global economic and trade activities are escalating. However, environmental problems and the emergence of green economy, a response to these problems, has led to the widespread introduction of green trade barriers. These barriers implicitly limit the development of trade activities. This paper focuses on the export difficulties caused by green trade barriers and proposes a method to quantify discrete product characteristics, explore the internal characteristics of commodities and decide optimally on intended export regions. Firstly, the discrete feature of products is quantified by quantitative transformation method. Secondly, the quantitative data are used to derive the best decision for export regions through support vector regression (SVR) method. Particle swarm optimisation is used in optimising SVR parameters to achieve high-precision decision making. Comparison with historical data from the industry park shows the identification accuracy of the optimised SVR model to be better than that of the traditional regression model. This finding presents a novel perspective for developing import and export under the background of green trade barriers.

Introducing GIS to TransNav and its Extensive Maritime Application: An Innovative Tool for Intelligent Decision Making?

Baylon A. M., Santos E. M. R.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

2013

Vol. 7, no. 4

557--566

This paper aims to introduce GIS, its definition, principle, application in any discipline particularly maritime, its process, data sets and features and its benefits to maritime and universities. Specifically, the paper intends to provide an overview of its wide applications in maritime including but not limited to marine transportation, marine environment, port management and operation, maritime education and training (MET) and maritime research. GIS simplest task is in mapping and visualization. But its most important function is in spatial analysis. Spatial analysis takes into account the location, geometry, topology, and relationships of geographic data, which lend itself to intelligent decision making. GIS is not just for researchers and students. GIS is especially useful for decision makers such as: managers, administrators, and directors of large and small projects. Scenarios are “seen” and analyzed even before events happen. To planners and decision makers, this is very important because they can assess the impact of events or scenario and may save a lot of time, effort, and money before implementing the actual project. An additional skill on GIS when learned or thought would certainly result to a technically competent maritime global workforce. The paper would provide ideas on possible areas for collaborations among TransNav member institutions for data sharing which may be processed and analyzed by a GIS specialist.