使用萤火虫、人工蜂群和基于遗传算法的人工神经网络进行日溪流预报的比较研究

IF 2.3 4区 地球科学
Huseyin Cagan Kilinc, Bulent Haznedar, Okan Mert Katipoğlu, Furkan Ozkan
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引用次数: 0

摘要

水资源管理和河流流量建模在环境研究中占有重要地位。它们是人类社会与其居住的脆弱生态系统之间的重要桥梁。由于水文系统建模具有相当大的挑战性,因此学者们一直致力于利用人工智能为河流流量预测提供更有效的方法。本研究主要侧重于探索混合模型在建立日流量数据与前瞻性数据之间的联系方面的预测能力。在研究中,将上述算法(萤火虫算法(FFA)、人工蜂群算法(ABC)、遗传算法(GA))与人工神经网络(ANN)模型进行了混合,并对科尼亚闭合流域的站点进行了数据分析。根据一系列图形和统计指标,对 FFA-ANN、GA-ANN、ABC-ANN 和长短期记忆 (LSTM) 模型进行了比较分析,以进行日流量预报。结果表明,FFA-ANN 混合模型的性能普遍优于其他模型和深度学习算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A comparative study of daily streamflow forecasting using firefly, artificial bee colony, and genetic algorithm-based artificial neural network

A comparative study of daily streamflow forecasting using firefly, artificial bee colony, and genetic algorithm-based artificial neural network

The management of water resources and the modeling of river flow have a prominent position within environmental research. They form a critical bridge between human societies and the delicate ecosystems they inhabit. Scholars have focused on benefiting more efficient methods based on the use of artificial intelligence for river flow forecasting, notably because modeling hydrological systems is quite challenging. This study primarily centered on exploring the predictive capacities of hybrid models in establishing a link between daily flow data and prospective data. In the study, the mentioned algorithms, firefly algorithm (FFA), artificial bee colony (ABC), genetic algorithm (GA), were hybridized with the artificial neural network (ANN) model and data analyzes were examined with the stations in the Konya Closed Basin. A comparative analysis of FFA–ANN, GA–ANN, ABC–ANN, and long short-term memory (LSTM) models was conducted for daily flow forecasting for daily flow forecasting according to a range of graphical and statistical metrics. The outcomes indicate that the FFA–ANN hybrid model generally performed better than other models and the deep learning algorithm.

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来源期刊
Acta Geophysica
Acta Geophysica GEOCHEMISTRY & GEOPHYSICS-
CiteScore
3.80
自引率
13.00%
发文量
251
期刊介绍: Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.
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