Corrigendum to: Optimization of Input Variables for Salinity Modeling in the Nakdong River Estuary Using Exploratory Data Analysis

Article information

J. Ocean Eng. Technol. 2025;39(6):699-699
Publication date (electronic) : 2025 December 15
doi : https://doi.org/10.26748/KSOE.2025.013c1
1Professor, Department of Civil and Envirionmental Engineering, Konkuk University, Seoul, Republic of Korea
2Researcher, Industry-University Cooperation Foundation, Inje University, Gimhae, Gyeongsangnam-do, Republic of Korea
3Professor, Department of Business Administration, Tech University of Korea, Gyeonggi-do, Republic of Korea
4CEO, Haekwang Eng., Haenam-Gun, Jeollanam-do, Republic of Korea
5Professor, Department of Fire and Disaster Prevention Engineering, Inje University, Gimhae, Gyeongsangnam-do, Republic of Korea
Corresponding author Jong-Sung Yoon: +82-55-320-3434, civyunjs@inje.ac.kr
Received 2025 November 7; Revised 2025 November 7; Accepted 2025 December 12.

Corrogendum to: Journal of Ocean Engineering and Technology, 39(4), 379–393, August, 2025 https://doi.org/10.26748/KSOE.2025.013

1. Introduction

In the originally published version of the article “Optimization of Input Variables for Salinity Modeling in the Nakdong River Estuary Using Exploratory Data Analysis” in volume 39 on page 393, There was an error in the funding statement. The corrected funding information is provided follow. This correction does not affect the scientific conclusions of the article.

2. Corrections

Location: Page 393, Funding

Correct the funding statement as shown in Table 1.

Correction of the funding statement

3. Closing

The authors apologize for this error and any inconvenience it may have caused.

Date of corrigendum: November 7, 2025

Article information Continued

Table 1

Correction of the funding statement

Item Finding
Incorrect This research was supported by the National Research Foundation of Korea (NRF) funded by the government (Ministry of Science and ICT) (No. 202301190002).
Correct This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2023-NR076807).