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Xuanzhi Liao, Shahnorbanun Sahran, Azizi Abdullah and Syaimak Abdul Shukor
Adaptive gradient descent methods such as Adam, RMSprop, and AdaGrad achieve great success in training deep learning models. These methods adaptively change the learning rates, resulting in a faster convergence speed. Recent studies have shown their prob...
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Yuhao Jing, Yang Wu, Jiwei Tang, Pingfang Zhou and Dengping Duan
The contribution of this paper is the proposal of a new receding horizon trajectory generation method for stratospheric airships? return phase. Since the energy consumption, wind field and path constraints are restrictions during the return phase of airs...
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Aminurrashid Noordin, Mohd Ariffanan Mohd Basri and Zaharuddin Mohamed
A micro air vehicle (MAV) is physically lightweight, such that even a slight perturbation could affect its attitude and position tracking. To attain better autonomous flight system performance, MAVs require good control strategies to maintain their attit...
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Kseniia Bazilevych, Ievgen Meniailov, Dmytro Chumachenko
Pág. 5 - 13
Subject: the use of the mathematical apparatus of neural networks for the scientific substantiation of anti-epidemic measures in order to reduce the incidence of diseases when making effective management decisions. Purpose: to apply cluster analysis, bas...
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Georgiana Magu, Radu Lucaciu and Alexandru Isar
A way to reduce the uncertainty at the output of a Kalman filter embedded into a tracker connected to an automotive RADAR sensor consists of the adaptive selection of parameters during the tracking process. Different informed strategies for automatically...
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Lin Zhang, Yian Zhu, Xianchen Shi and Xuesi Li
To improve the intelligence and accuracy of the Situation Assessment (SA) in complex scenes, this work develops an improved fuzzy deep neural network approach to the situation assessment for multiple Unmanned Aerial Vehicle(UAV)s. Firstly, this work norm...
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Yong Han, Cheng Wang, Yibin Ren, Shukang Wang, Huangcheng Zheng and Ge Chen
The accurate prediction of bus passenger flow is the key to public transport management and the smart city. A long short-term memory network, a deep learning method for modeling sequences, is an efficient way to capture the time dependency of passenger f...
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