应用人工神经网络预测埋地矩形箱形承载管道的横向和上浮能力

IF 2 4区工程技术 Q3 ENGINEERING, GEOLOGICAL

Marine Georesources & Geotechnology Pub Date : 2024-01-05 DOI:10.1080/1064119x.2023.2300046

Khamnoy Kounlavong, Van Qui Lai, Jitesh T. Chavda, Rungkhun Banyong, Pitthaya Jamsawang, Suraparb Keawsawasvong

引用次数: 0

摘要

目前，城市和近海地下综合管线作为基础设施被频繁使用，以安装用于电力、信号传输、水利和交通的不同工程管线。

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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Application of artificial neural networks for predicting lateral and uplift capacity of buried rectangular box carrying pipelines

Urban and offshore subterranean comprehensive pipelines are currently utilized frequently as infrastructure for fitting different engineering pipelines used for electricity, signal transmission, na...

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来源期刊

Marine Georesources & Geotechnology 工程技术-工程：大洋

CiteScore

5.30

自引率

13.60%

发文量

审稿时长

>12 weeks

期刊介绍： Marine Georesources & Geotechnology publishes research applied to the scientific and engineering aspects, and the management and utilization, of seafloor sediments and rocks. The journal is intended for researchers and engineers, in both academia and industry, who seek solutions to problems in marine mineral resources and civil engineering. Areas covered range from marine minerals exploration and recovery to anchoring and mooring systems, bottom installations, and coastal engineering structures. The journal includes the study of acoustical, biological, chemical, mechanical, and physical properties affecting the geological system of the seafloor and response of this system to applied static and dynamic loads. Special emphasis is placed on the environmental aspects of seafloor exploration and development. The journal accepts contributions on topics such as shipboard mining systems, seafloor lodes, nodules, phosphates, crusts and placers, pipelines, platforms, and processing and transportation, as well as analytic techniques related to marine mining.