Erratum to “Evaluating the Rate of Penetration With Deep-Learning Predictive Models”

IF 4.3 3区工程技术 Q2 ENERGY & FUELS

International Journal of Energy Research Pub Date : 2025-08-28 DOI:10.1155/er/9813497

引用次数: 0

Abstract

C. Lee, J. Kim, N. Kim, S. Ki, J. Seo, and C. Park, “Evaluating the Rate of Penetration With Deep-Learning Predictive Models,”International Journal of Energy Research 2025 (2025): 8872793, https://doi.org/10.1155/er/8872793.

In the article titled “Evaluating the Rate of Penetration With Deep-Learning Predictive Models,” there was an error in Figure 10. The x-axis titles in the images to the right in Figure 10a–c were ROP (measured) instead of ROP (predicted). The corrected figure is shown below and is listed as Figure 1:

We apologize for this error.

Abstract Image

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对“用深度学习预测模型评估渗透率”的勘误

C. Lee， J. Kim， N. Kim， S. Ki， J. Seo，和C. Park，“用深度学习预测模型评估渗透率”，International Journal of Energy Research 2025 (2025): 8872793, https://doi.org/10.1155/er/8872793.In文章标题为“用深度学习预测模型评估渗透率”，图10中有一个错误。图10a-c中右侧图像的x轴标题为ROP（实测），而不是ROP（预测）。更正后的图如下图1所示：我们为这个错误道歉。

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

International Journal of Energy Research 工程技术-核科学技术

CiteScore

9.80

自引率

8.70%

发文量

1170

审稿时长

3.1 months

期刊介绍： The International Journal of Energy Research (IJER) is dedicated to providing a multidisciplinary, unique platform for researchers, scientists, engineers, technology developers, planners, and policy makers to present their research results and findings in a compelling manner on novel energy systems and applications. IJER covers the entire spectrum of energy from production to conversion, conservation, management, systems, technologies, etc. We encourage papers submissions aiming at better efficiency, cost improvements, more effective resource use, improved design and analysis, reduced environmental impact, and hence leading to better sustainability. IJER is concerned with the development and exploitation of both advanced traditional and new energy sources, systems, technologies and applications. Interdisciplinary subjects in the area of novel energy systems and applications are also encouraged. High-quality research papers are solicited in, but are not limited to, the following areas with innovative and novel contents: -Biofuels and alternatives -Carbon capturing and storage technologies -Clean coal technologies -Energy conversion, conservation and management -Energy storage -Energy systems -Hybrid/combined/integrated energy systems for multi-generation -Hydrogen energy and fuel cells -Hydrogen production technologies -Micro- and nano-energy systems and technologies -Nuclear energy -Renewable energies (e.g. geothermal, solar, wind, hydro, tidal, wave, biomass) -Smart energy system