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Andrea Momblanch, Ian P. Holman and Sanjay K. Jain
Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himala...
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Bao She, Jiating Hu, Linsheng Huang, Mengqi Zhu and Qishuo Yin
To grasp the spatial distribution of soybean planting areas in time is the prerequisite for the work of growth monitoring, crop damage assessment and yield estimation. The research on remote sensing identification of soybean conducted in China mainly foc...
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Liangkun Yu, Xiang Sun, Rana Albelaihi and Chen Yi
Federated learning (FL) is a collaborative machine-learning (ML) framework particularly suited for ML models requiring numerous training samples, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Random Forest, in the co...
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Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const...
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Yusuf Guzel, Gaetano Elia, Mohamed Rouainia and Gaetano Falcone
A key issue for the estimation of ground shaking is the proper selection of input motions at the seismic bedrock. At the same time, the effect of the input motion scaling strategy on structural response is typically studied disregarding the presence of t...
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Abdulaziz AlMohimeed, Hager Saleh, Sherif Mostafa, Redhwan M. A. Saad and Amira Samy Talaat
Cervical cancer affects more than half a million women worldwide each year and causes over 300,000 deaths. The main goals of this paper are to study the effect of applying feature selection methods with stacking models for the prediction of cervical canc...
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Fatma Yaprakdal and Merve Varol Arisoy
In the smart grid paradigm, precise electrical load forecasting (ELF) offers significant advantages for enhancing grid reliability and informing energy planning decisions. Specifically, mid-term ELF is a key priority for power system planning and operati...
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Woochul Choi, Bongjoo Jang, Intaek Jung, Hongki Sung and Younmi Jang
Research related to thermal cameras, which are major control measures, is increasing to overcome the limitations of closed-circuit television (CCTV) images. Thermal cameras have the advantage of easily detecting objects at night and of being able to iden...
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Duo Sun, Lei Zhang, Kai Jin, Jiasheng Ling and Xiaoyuan Zheng
Aiming at the imbalance of industrial control system data and the poor detection effect of industrial control intrusion detection systems on network attack traffic problems, we propose an ETM-TBD model based on hybrid machine learning and neural network ...
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Jun Wu, Xi Wang, Limin Huang, Ziyu Wang, Da Wan and Pengbo Li
With the extensive application of data analysis in various parts of the landscape design process, Building Information Modeling (BIM), City Information Modeling (CIM), and Landscape Information Modeling (LIM) all aim to achieve key data sharing and colla...
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