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Mohammad Javad Moradi, Mohammad Mahdi Roshani, Amirhosein Shabani and Mahdi Kioumarsi
As a lateral load-bearing system, the steel plate shear wall (SPSW) is utilized in different structural systems that are susceptible to seismic risk and because of functional reasons SPSWs may need openings. In this research, the effects of rectangular o...
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Wen-Yeau Chang
High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting ...
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Zhiyao Zhu, Huilong Ren, Xiuhuan Wang, Nan Zhao and Chenfeng Li
The limit state function is important for the assessment of the longitudinal strength of damaged ships under combined bending moments in severe waves. As the limit state function cannot be obtained directly, the common approach is to calculate the result...
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Jian Cao, Yang Zhang, Chuanyu Ju, Xinyi Xue and Jiyuan Zhang
With the continuous development of the space industry, the demand for low-gravity simulation experiments on the ground for spacecraft is increasing, to overcome the gravity compensation of spacecraft on the ground tests. This paper presents a new low-gra...
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Ioannis G. Tsoulos and Vasileios Charilogis
In the present work, an innovative two-phase method is presented for parameter tuning in radial basis function artificial neural networks. These kinds of machine learning models find application in many scientific fields in classification problems or in ...
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Bingbing Qiu, Guofeng Wang, Yunsheng Fan, Dongdong Mu and Xiaojie Sun
In the presence of modeling uncertainties and input saturation, this paper proposes a practical adaptive sliding mode control scheme for an underactuated unmanned surface vehicle (USV) using neural network, auxiliary dynamic system, sliding mode control ...
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Hossein Komijani, Sepideh Rezaeihassanabadi, Mohammad Reza Parsaei, Saeed Maleki
Pág. 128 - 132
Simulation and preparing predictive model of electrochemical impedance Nyquist plots based on radial basis function neural network (RBFNN) are presented in this paper. The RBFNN as a powerful predictive system predicts the real and imaginary parts of imp...
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Junting Wang, Tianhe Xu, Wei Huang, Liping Zhang, Jianxu Shu, Yangfan Liu and Linyang Li
Underwater sound speed is one of the most significant factors that affects high-accuracy underwater acoustic positioning and navigation. Due to its complex temporal variation, the forecasting of the underwater sound speed field (SSF) becomes a challengin...
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Yunfei Yang, Haiwen Tu, Lei Song, Lin Chen, De Xie and Jianglong Sun
Resistance is one of the important performance indicators of ships. In this paper, a prediction method based on the Radial Basis Function neural network (RBFNN) is proposed to predict the resistance of a 13500 transmission extension unit (13500TEU) conta...
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Kai Xu, Gang Wang, Luyao Zhang, Liquan Wang, Feihong Yun, Wenhao Sun, Xiangyu Wang and Xi Chen
In this study, an annular jet pump optimization method is proposed based on an RBF(Radial Basis Function) neural network model and NSGA-II(Non-Dominated Sorting Genetic Algorithm) optimization algorithm to improve the hydraulic performance of the annular...
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Jichao Liu, Cheng Wang, Peiyu Zhang, Min Gui, Lijia Tong and Bin Li
Aluminizing is a common protective coating for aeroengine turbine blades, but there is no method to accurately measure the aluminized thickness. X-ray fluorescence nondestructive testing technology is a method which can basically realize the measurement ...
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Minghui Zhao, Xiaobin Xu, Hao Yang and Zhijie Pan
A new proportional integral derivative (PID) control method is proposed for the 3D laser scanning system converted from 2D Lidar with a pitching motion device. It combines the advantages of a fuzzy algorithm, a radial basis function (RBF) neural network ...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Xi Zhang and Hui Lin
This paper proposes an adaptive backstepping control algorithm for electric braking systems with electromechanical actuators (EMAs). First, the ideal mathematical model of the EMA is established, and the nonlinear factors are analyzed, such as the deform...
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Sendren Sheng-Dong Xu, Hsu-Chih Huang, Tai-Chun Chiu and Shao-Kang Lin
This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called th...
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Duc-Thien Tran, Minh-Nhat Nguyen and Kyoung Kwan Ahn
An electrohydraulic elastic manipulator (EEM) is a kind of variable stiffness system (VSS). The equilibrium position and stiffness controller are the two main problems which must be considered in the VSS. When the system stiffness is changed for a specif...
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Mohammad Jafari and Hao Xu
Stabilizing the Unmanned Aircraft Systems (UAS) under complex environment including system uncertainties, unknown noise and/or disturbance is so challenging. Therefore, this paper proposes an adaptive neural network based intelligent control method to ov...
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Mohammad Jafari and Hao Xu
Stabilizing the Unmanned Aircraft Systems (UAS) under complex environment including system uncertainties, unknown noise and/or disturbance is so challenging. Therefore, this paper proposes an adaptive neural network based intelligent control method to ov...
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Lei Sun, Honglei An, Hongxu Ma, Qing Wei and Jialong Gao
Lower limb knee?ankle prostheses can effectively assist above-knee amputees in completing their basic daily activities. This study explored methods for estimating the joint kinematics of intelligent lower limb prostheses to better adapt them to the walki...
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Duc-Anh Pham and Seung-Hun Han
The sliding mode controller stands out for its exceptional stability, even when the system experiences noise or undergoes time-varying parameter changes. However, designing a sliding mode controller necessitates precise knowledge of the object?s exact mo...
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