利用人工神经网络和公民科学数据评估沿海地区的水母存在情况

IF 5 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION
J. Castro-Gutiérrez, J. C. Gutiérrez-Estrada, J. C. Báez
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引用次数: 0

摘要

沿海地区的水母潮会给海滩使用者和地方当局带来巨大挑战。了解影响水母出现的因素对于制定有效的管理和缓解策略至关重要。本研究利用安达卢西亚海岸(40 个不同地区的 232 个海滩)的公民科学数据和机器学习技术,研究是否可以预测沿海地区是否存在水母。采用多层感知器(MLP)神经网络对用户关于水母存在与否的评论进行分类,准确率约为 96%。MLP 模型在处理非线性分类问题和噪声方面表现出很强的鲁棒性,但在预测水母是否存在方面精度较低,这可能是由于数据集的不平衡造成的。研究还纳入了环境数据,以确定海面温度、风向和风速对水母分布的影响。结果与之前的研究一致,表明这些环境因素对水母的出现有显著影响。综述与应用。这项研究为海滩管理提供了可行的建议。对海面温度和风力条件进行连续监测,将能更准确地预测水母的分布。动态响应环境数据的适应性管理策略将有助于减轻水母水华对沿海旅游业和公众健康的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas

Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas

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来源期刊
Journal of Applied Ecology
Journal of Applied Ecology 环境科学-生态学
CiteScore
9.80
自引率
3.50%
发文量
229
审稿时长
4.5 months
期刊介绍: Journal of Applied Ecology publishes novel, high-impact papers on the interface between ecological science and the management of biological resources.The editors encourage contributions that use applied ecological problems to test and develop basic theory, although there must be clear potential for impact on the management of the environment.
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