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Anthony A. Amori, Olufemi P. Abimbola, Trenton E. Franz, Daran Rudnick, Javed Iqbal and Haishun Yang
Model calibration is essential for acceptable model performance and applications. The Hybrid-Maize model, developed at the University of Nebraska-Lincoln, is a process-based crop simulation model that simulates maize growth as a function of crop and fiel...
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Amr A. Abd El-Mageed, Ayoub Al-Hamadi, Samy Bakheet and Asmaa H. Abd El-Rahiem
It is difficult to determine unknown solar cell and photovoltaic (PV) module parameters owing to the nonlinearity of the characteristic current?voltage (I-V) curve. Despite this, precise parameter estimation is necessary due to the substantial effect par...
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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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Wen Gao, Yanqiang Bi, Xiyuan Li, Apeng Dong, Jing Wang and Xiaoning Yang
Hybrid airships, combining aerodynamic lift and buoyant lift, are efficient near-space aircraft for scientific exploration, observation, and surveillance. Compared to conventional airplanes and airships, hybrid airships offer unique advantages, including...
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Hosang Han and Jangwon Suh
The accurate prediction of soil contamination in abandoned mining areas is necessary to address their environmental risks. This study employed a combined model of machine learning and geostatistics to predict the spatial distribution of soil contaminatio...
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Tahsin Koroglu and Elanur Ekici
In recent years, wind energy has become remarkably popular among renewable energy sources due to its low installation costs and easy maintenance. Having high energy potential is of great importance in the selection of regions where wind energy investment...
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Ishaq Hafez and Rached Dhaouadi
This study presents hybrid particle swarm optimization with quasi-Newton (HPSO-QN), a hybrid optimization method for accurately identifying mechanical parameters in two-mass model (2MM) systems. These systems are commonly used to model and control high-p...
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Mei-Yan Zhuo, Jinn-Chyi Chen, Ren-Ling Zhang, Yan-Kun Zhan and Wen-Sun Huang
In this study, a seepage prediction model was established for roller-compacted concrete dams using support vector regression (SVR) with hybrid parameter optimization (HPO). The model includes data processing via HPO and machine learning through SVR. HPO ...
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Qianqian Xia, Wenyi Zhang, Bing Qi and Yunxia Wang
In order to meet the sowing demand of the hybrid rice plug seedling, a horizontal rotary precision seed metering device was proposed. The key structure parameters were designed, the kinematics analysis of the seed-filling process was carried out, and the...
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Rahmeh Ibrahim, Rawan Ghnemat and Qasem Abu Al-Haija
Convolutional Neural Networks (CNNs) have exhibited remarkable potential in effectively tackling the intricate task of classifying MRI images, specifically in Alzheimer?s disease detection and brain tumor identification. While CNNs optimize their paramet...
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