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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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Pablo de Llano, Carlos Piñeiro, Manuel Rodríguez
Pág. pp. 163 - 198
This paper offers a comparative analysis of the effectiveness of eight popular forecasting methods: univariate, linear, discriminate and logit regression; recursive partitioning, rough sets, artificial neural networks, and DEA. Our goals are: clarify the...
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Jose M. Bernal-de-Lázaro
Pág. 74 - 81
This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis syste...
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Aymane Ahajjam, Jaakko Putkonen, Emmanuel Chukwuemeka, Robert Chance and Timothy J. Pasch
Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weathe...
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Sachin Gowda, Vaishakh Kunjar, Aakash Gupta, Govindaswamy Kavitha, Bishnu Kant Shukla and Parveen Sihag
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional labora...
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Liyuan Zhang, Xiaoying Song, Yaxiao Niu, Huihui Zhang, Aichen Wang, Yaohui Zhu, Xingye Zhu, Liping Chen and Qingzhen Zhu
As prior information for precise nitrogen fertilization management, plant nitrogen content (PNC), which is obtained timely and accurately through a low-cost method, is of great significance for national grain security and sustainable social development. ...
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Z. Jason Hou, Nicholas D. Ward, Allison N. Myers-Pigg, Xinming Lin, Scott R. Waichler, Cora Wiese Moore, Matthew J. Norwood, Peter Regier and Steven B. Yabusaki
The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine ...
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Yang Liu and Qianqian Zhang
Analyzing 165 data from five national control sites in Baiyangdian Lake, this study unveils its spatiotemporal pattern of water quality. Utilizing machine learning and multivariate statistical techniques, this study elucidates the effects of rainfall and...
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Kidoo Park, Yeongjeong Seong, Younghun Jung, Ilro Youn and Cheon Kyu Choi
The methods for improving the accuracy of water level prediction were proposed in this study by selecting the Gated Recurrent Unit (GRU) model, which is effective for multivariate learning at the Paldang Bridge station in Han River, South Korea, where th...
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Sarra Bel Haj Salem, Aissam Gaagai, Imed Ben Slimene, Amor Ben Moussa, Kamel Zouari, Krishna Kumar Yadav, Mohamed Hamdy Eid, Mostafa R. Abukhadra, Ahmed M. El-Sherbeeny, Mohamed Gad, Mohamed Farouk, Osama Elsherbiny, Salah Elsayed, Stefano Bellucci and Hekmat Ibrahim
In the Zeroud basin, a diverse array of methodologies were employed to assess, simulate, and predict the quality of groundwater intended for irrigation. These methodologies included the irrigation water quality indices (IWQIs); intricate statistical anal...
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