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Minychl G. Dersseh, Aron A. Kibret, Seifu A. Tilahun, Abeyou W. Worqlul, Mamaru A. Moges, Dessalegn C. Dagnew, Wubneh B. Abebe and Assefa M. Melesse
Water hyacinth is a well-known invasive weed in lakes across the world and harms the aquatic environment. Since 2011, the weed has invaded Lake Tana substantially posing a challenge to the ecosystem services of the lake. The major factors which affect th...
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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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Olga Kulesha and Harsha Ratnaweera
The membrane bioreactor (MBR) and the biofilm membrane bioreactor (BF-MBR) are among key solutions to water scarcity; however, membrane fouling is the major bottleneck for any expansion of these technologies. Prepolymerized aluminum coagulants tend to ex...
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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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Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
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Haibo Chu, Zhuoqi Wang and Chong Nie
Accurate and reliable monthly streamflow prediction plays a crucial role in the scientific allocation and efficient utilization of water resources. In this paper, we proposed a prediction framework that integrates the input variable selection method and ...
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Abdullah F. Al-Aboosi, Aldo Jonathan Muñoz Vazquez, Fadhil Y. Al-Aboosi, Mahmoud El-Halwagi and Wei Zhan
Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intellig...
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Muh Farid, Muhammad Fuad Anshori, Riccardo Rossi, Feranita Haring, Katriani Mantja, Andi Dirpan, Siti Halimah Larekeng, Marlina Mustafa, Adnan Adnan, Siti Antara Maedhani Tahara, Nirwansyah Amier, M. Alfan Ikhlasul Amal and Andi Isti Sakinah
The fruit weight is an important guideline for breeders and farmers to increase marketable productions, although conventionally it requires destructive measurements. The combination of image-based phenotyping (IBP) approaches with multivariate analysis h...
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Onggarbek Alipbeki, Chaimgul Alipbekova, Gauhar Mussaif, Pavel Grossul, Darima Zhenshan, Olesya Muzyka, Rimma Turekeldiyeva, Dastan Yelubayev, Daniyar Rakhimov, Przemyslaw Kupidura and Eerassyl Aliken
Changes occurring because of human activity in protected natural places require constant monitoring of land use (LU) structures. Therefore, Korgalzhyn District, which occupies part of the Korgalzhyn State Natural Reserve territory, is of considerable int...
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Ilia Zaznov, Julian Martin Kunkel, Atta Badii and Alfonso Dufour
This paper introduces a novel deep learning approach for intraday stock price direction prediction, motivated by the need for more accurate models to enable profitable algorithmic trading. The key problems addressed are effectively modelling complex limi...
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