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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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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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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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Veljko Marinkovic, Darko Dimitrovski, Vladimir Senic
Research question: The aim of the paper is to identify the statistically significant drivers for gold panning revisit intention at the River Pek in Serbia as one of the key factors in determining a positive effect on the destination?s economic sustainabi...
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Jiangtao Chen, Jiao Zhao, Wei Xiao, Luogeng Lv, Wei Zhao and Xiaojun Wu
Given the randomness inherent in fluid dynamics problems and limitations in human cognition, Computational Fluid Dynamics (CFD) modeling and simulation are afflicted with non-negligible uncertainties, casting doubts on the credibility of CFD. Scientifica...
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Kangwen Sun, Siyu Liu, Huafei Du, Haoquan Liang and Xiao Guo
The stratospheric airship is a type of aerostat that uses solar energy as its power source and can fly continuously for months or even years in near space. The rapid and accurate prediction of the output power of its solar array is the key to maintaining...
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Jiahao Fan and Weijun Pan
In recent years, automatic speech recognition (ASR) technology has improved significantly. However, the training process for an ASR model is complex, involving large amounts of data and a large number of algorithms. The task of training a new model for a...
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Zhifu Lin, Dasheng Xiao and Hong Xiao
Flow through complex thermodynamic machinery is intricate, incorporating turbulence, compressibility effects, combustion, and solid?fluid interactions, posing a challenge to classical physics. For example, it is not currently possible to simulate a three...
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Javensius Sembiring, Rianto Adhy Sasongko, Eduardo I. Bastian, Bayu Aji Raditya and Rayhan Ekananto Limansubroto
This paper investigates the development of a deep learning-based flight control model for a tilt-rotor unmanned aerial vehicle, focusing on altitude, speed, and roll hold systems. Training data is gathered from the X-Plane flight simulator, employing a p...
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Bocheng Zhao, Mingying Huo, Ze Yu, Naiming Qi and Jianfeng Wang
In this study, we propose an aerial rendezvous method to facilitate the recovery of unmanned aerial vehicles (UAVs) using carrier aircrafts, which is an important capability for the future use of UAVs. The main contribution of this study is the developme...
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