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M.H.J.P. Gunarathna, Kazuhito Sakai, Tamotsu Nakandakari, Kazuro Momii and M.K.N. Kumari
Poor data availability on soil hydraulic properties in tropical regions hampers many studies, including crop and environmental modeling. The high cost and effort of measurement and the increasing demand for such data have driven researchers to search for...
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Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
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Haekyung Park and Dong Kun Lee
Korea experienced an unexpected drought in the southern Seoul metropolitan area from 2015 to 2017. After that, the Korean government has been drafting various policies to mitigate the effects of drought. However, these are primarily long-term drought pol...
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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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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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Zhenzhen Di, Miao Chang, Peikun Guo, Yang Li and Yin Chang
Most worldwide industrial wastewater, including in China, is still directly discharged to aquatic environments without adequate treatment. Because of a lack of data and few methods, the relationships between pollutants discharged in wastewater and those ...
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Ognjen Radovic,Srdan Marinkovic,Jelena Radojicic
Credit scoring attracts special attention of financial institutions. In recent years, deep learning methods have been particularly interesting. In this paper, we compare the performance of ensemble deep learning methods based on decision trees with the b...
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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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Hugo López-Fernández
Pág. 22 - 25
Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS) has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This a...
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Rejath Jose, Faiz Syed, Anvin Thomas and Milan Toma
The advancement of machine learning in healthcare offers significant potential for enhancing disease prediction and management. This study harnesses the PyCaret library?a Python-based machine learning toolkit?to construct and refine predictive models for...
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