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Hamed Taherdoost and Mitra Madanchian
In recent years, artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. This comparative review investigates the evolving landscape of AI advancements, providing a thorough e...
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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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Jia-Ling Xie, Wei-Feng Shi, Ting Xue and Yu-Hang Liu
The fault detection and diagnosis of a ship?s electric propulsion system is of great significance to the reliability and safety of large modern ships. The traditional fault diagnosis method based on mathematical models and expert knowledge is limited by ...
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Alexey Liogky and Victoria Salamatova
Data-driven simulations are gaining popularity in mechanics of biomaterials since they do not require explicit form of constitutive relations. Data-driven modeling based on neural networks lacks interpretability. In this study, we propose an interpretabl...
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Zilin Zhao, Zhi Cai, Mengmeng Chang and Zhiming Ding
Unconventional events exacerbate the imbalance between regional transportation demand and limited road network resources. Scientific and efficient path planning serves as the foundation for rapidly restoring equilibrium to the road network. In real large...
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Anni Zhao, Arash Toudeshki, Reza Ehsani, Joshua H. Viers and Jian-Qiao Sun
The Delta robot is an over-actuated parallel robot with highly nonlinear kinematics and dynamics. Designing the control for a Delta robot to carry out various operations is a challenging task. Various advanced control algorithms, such as adaptive control...
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Cai Wu, Yanwen Wang, Jiong Wang, Menno-Jan Kraak and Mingshu Wang
This study introduces a machine learning-based framework for mapping street patterns in urban morphology, offering an objective, scalable approach that transcends traditional methodologies. Focusing on six diverse cities, the research employed supervised...
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Jeongeun Won, Jiyu Seo, Jeonghoon Lee, Jeonghyeon Choi, Yoonkyung Park, Okjeong Lee and Sangdan Kim
River runoff predictions in ungauged basins are one of the major challenges in hydrology. In the past, the approach using a physical-based conceptual model was the main approach, but recently, a solution using a data-driven model has been evaluated as mo...
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Vaia I. Kontopoulou, Athanasios D. Panagopoulos, Ioannis Kakkos and George K. Matsopoulos
In the broad scientific field of time series forecasting, the ARIMA models and their variants have been widely applied for half a century now due to their mathematical simplicity and flexibility in application. However, with the recent advances in the de...
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Duc-Thinh Ngo, Ons Aouedi, Kandaraj Piamrat, Thomas Hassan and Philippe Raipin-Parvédy
As the complexity and scale of modern networks continue to grow, the need for efficient, secure management, and optimization becomes increasingly vital. Digital twin (DT) technology has emerged as a promising approach to address these challenges by provi...
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