Results 31 to 40 of about 10,610,136 (340)
IEEE Transactions on Computational Social Systems, 2023 This article proposes an agent-based policy simulation framework that can be applied to the cases satisfying: 1) the agents try to maximize some intertemporal preference and 2) the impacts of different factors on agents’ behavioral tendency are monotonic.
Songming Yu
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BP Neural Network Fuse with Morphology Edge Detection Method
Journal of Harbin University of Science and Technology, 2021 In order to obtain better image edge information, an edge detection algorithm combining BP (Back Propagation) neural network and morphology is proposed.
YUE Xin-hua, DENG Cai-xia, ZHANG Zhao-ru
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Robustness enhancement study of augmented positive identification controller by a sigmoid function
IAES International Journal of Artificial Intelligence (IJ-AI), 2023 The dissolved oxygen concentration in the wastewater treatment process (WWTP) must remain in a specific range while the factory operates. The augmented positive identification (PID) controller with a nonlinear element (sigmoid function) is proposed to ...
Abbas H. Issa +3 more
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Handling Vanishing Gradient Problem Using Artificial Derivative
IEEE Access, 2021 Sigmoid function and ReLU are commonly used activation functions in neural networks (NN). However, sigmoid function is vulnerable to the vanishing gradient problem, while ReLU has a special vanishing gradient problem that is called dying ReLU problem ...
Zheng Hu, Jiaojiao Zhang, Yun Ge
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Designing novel LDO voltage regulator implementation on FPGA using neural network [PDF]
Journal of Applied Research on Industrial Engineering, 2021 This paper describes a new technique for implementing an Artificial Neural Network (ANN) using Field Programmable Gate Array (FPGA). The goal is design the Low Drop Output (LDO) voltage-regulator circuit with the desired features depending on the ...
Mahdieh Jahangiri +2 more
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Jurnal Serambi Engineering, 2022 Neural network Backpropagation is a good method to use to determine RGB color (Red, Green, Blue) because it can give high accuracy values. Neural network backpropagation there are several activation functions that can be used.
Ikhwan Pamungkas +2 more
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An effective vehicle road scene recognition based on improved deep learning
Measurement: Sensors, 2023 In order to improve the recognition for autonomous vehicles with respect to road scenes, a new activation function called ReLU sigmoid is proposed based on ReLU and the sigmoid model, which resolves the issue of neuron necrosis in the ReLU model. Through
Qiaojun Li, Wei Yang
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A Flexible Sigmoid Function of Determinate Growth [PDF]
Annals of Botany, 2002 A new empirical equation for the sigmoid pattern of determinate growth, 'the beta growth function', is presented. It calculates weight (w) in dependence of time, using the following three parameters: t(m), the time at which the maximum growth rate is obtained; t(e), the time at the end of growth; and w(max), the maximal value for w, which is achieved ...
Yin, X. +4 more
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Sigmoid functions for the smooth approximation to the absolute value function [PDF]
Moroccan Journal of Pure and Applied Analysis, 2020 Abstract We present smooth approximations to the absolute value function |x| using sigmoid functions. In particular, x erf(x/μ) is proved to be a better smooth approximation for |x| than x tanh(x/μ) and
Yogesh J. Bagul, Christophe Chesneau
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Algorithms, 2023 Planning an achievable trajectory for a mobile robot usually consists of two steps: (i) finding a path in the form of a sequence of discrete waypoints and (ii) transforming this sequence into a continuous and smooth curve.
Svetlana A. Krasnova +3 more
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