Maritime Computing Transportation, Environment, and Development: Trends of Data Visualization and Computational Methodologies

Q3 Engineering
T. Chaichana
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引用次数: 0

Abstract

This research aims to characterize the field of maritime computing (MC) transportation, environment, and development. It is the first report to discover how MC domain configurations support management technologies. An aspect of this research is the creation of drivers of ocean-based businesses. Systematic search and meta-analysis are employed to classify and define the MC domain. MC developments were first identified in the 1990s, representing maritime development for designing sailboats, submarines, and ship hydrodynamics. The maritime environment is simulated to predict emission reductions, coastal waste particles, renewable energy, and engineer robots to observe the ocean ecosystem. Maritime transportation focuses on optimizing ship speed, maneuvering ships, and using liquefied natural gas and submarine pipelines. Data trends with machine learning can be obtained by collecting a big data of similar computational results for implementing artificial intelligence strategies. Research findings show that modeling is an essential skill set in the 21st century.
海事计算运输、环境与发展:数据可视化和计算方法的发展趋势
本研究旨在描述海事计算(MC)运输、环境和发展领域。这是第一份发现MC域配置如何支持管理技术的报告。这项研究的一个方面是创建基于海洋的企业的驱动因素。采用系统搜索和荟萃分析对MC领域进行分类和定义。MC的发展最早出现在20世纪90年代,代表了设计帆船、潜艇和船舶流体力学的海事发展。模拟海洋环境以预测减排、沿海废物颗粒、可再生能源,并设计机器人来观察海洋生态系统。海上运输侧重于优化船舶速度、操纵船舶以及使用液化天然气和海底管道。机器学习的数据趋势可以通过收集类似计算结果的大数据来实现人工智能策略。研究结果表明,建模是21世纪的一项基本技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advances in Technology Innovation
Advances in Technology Innovation Energy-Energy Engineering and Power Technology
CiteScore
1.90
自引率
0.00%
发文量
18
审稿时长
12 weeks
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