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[Abdul/허성구 통합,J.Water.Proc.Eng/JCR10%] 수질 TN/TP AI 소프트센서-XAI
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  • 2023-03-13

Hi EMSEL, 

I am pleased to inform you that  EMSEL Ph.D students, Abdulrahman H. Ba-Alawi, SungKu Heo and Roberto Chang, TaeYong Woo, MinHan Kim's paper has been published in the Journal of Water Process Engineering (ISSN: 2214-7144, IF=7.34, JCR TOP10% journal). 

Please give your big hands to Abdulrahman H. Ba-Alawi

Congratulations for the paper acceptance indeed.

Topic: AI-softsensor, total nitrogen and total phosphorus​, ​Missing data, convolutional auto-encoder , XAI(Explainable AI) 

 

연구실 논문 소식입니다. 

EMSEL 연구실 Abdul박사과정과 허성구/우태용 통합 과정, 김민한 박사과정 논문이 Journal of Water Process Engineering (IF=7.34, JCR TOP 10%: Water Resources)저널에 게재 l되었습니다. (주) 에이치코비와 공동과제 수행 중인  AI-softsensor 수질 TN/TP 소프트센서​ 개발로 2022년 실시간 데이타 안양천 총질소/총인 실시간 소프트센서에 관한 내용으로 최신 연구 결과입니다.  

- Abdulrahman H. Ba-Alawi, SungKu Heo, Hanaa Aamer, Roberto Chang, TaeYong Woo, MinHan Kim, ChangKyoo Yoo*, Development of transparent high-frequency soft sensor of total nitrogen and total phosphorus concentrations in rivers using stacked convolutional auto-encoder and explainable AIJournal of Water Process Engineering (ISSN: 2214-7144, SCIE, JCR TOP 10%: Water Resources), Elsevier, 53(7), pp.103661 (2023.7) (Ack (4): BK21, NRF 2021R1A2C2007838, a Graduate School specialized in Climate Change, 중기청-코비)

Highlights 

 An explainable DL model was used for first time for water nutrients monitoring. 

 Boruta algorithm identified the most influencing water quality features on TN and TP. 

 The CAE-DFC showed a superior prediction for TN and TP (R 2= 0.9607 and 0.9137).

 Explainable CAE-DFC based soft sensor outperformed SVR, DNN, RF, and XGBoost models. 

 XAI-based Kernel SHAP provided a clear interpretation of the CAE-DFC model outcome. 

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이전글 [Mohammad학생, ​Langmuir/IF4.3​] ML Prediction of Morphology in Polymer Particles​ ​[기계학습기반 고분자 입자 형상 예측, 이란 이스파한 과학기술대 공동연구]
다음글 [Pouya박사/Saman학생, ECM논문/JCR1.8%] 물-엑서지 통합분석기반 용수 및 전력생산 (water-exergy nexus analysis)