Suchergebnisse - Robust backpropagation learning algorithm

TAO-robust backpropagation learning algorithm von Pernía-Espinoza, Alpha V., Ordieres-Meré, Joaquín B., Martínez-de-Pisón, Francisco J., González-Marcos, Ana

“… ] with the backpropagation algorithm to produce the TAO-robust learning algorithm, in order to deal with the problems of modelling with outliers …”
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The annealing robust backpropagation (ARBP) learning algorithm von Chuang, C C, Su, S F, Hsiao, C C

“… Even though various robust learning algorithms have been proposed in the literature, those approaches still suffer from the initialization problem …”
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Neural networks with robust backpropagation learning algorithm von Walczak, B.

“… A robust error suppressor function, which is independent of the underlying probability density function and convenient for computer programs, is proposed to robustify the backpropagation learning …”
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A robust backpropagation learning algorithm for function approximation von Chen, D.S., Jain, R.C.

“… In this paper we derive a robust BP learning algorithm that is resistant to the noise effects and is capable of rejecting gross errors during the approximation process …”
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Robust optimization design method for structural reliability based on active-learning MPA-BP neural network von Dong, Zhao, Sheng, Ziqiang, Zhao, Yadong, Zhi, Pengpeng

“… redundancy in the design. In order to improve the accuracy and rationality of the design results, a robust design method for structural reliability based on an active-learning marine predator algorithm (MPA)–backpropagation (BP …”
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Comparison of different backpropagation training algorithms using robust M-estimators performance functions von Abd Ellah, Ali R., Essai, Mohamed H., Yahya, Ahmed

“… Many robust learning algorithms have been proposed so far to improve the performance of neural networks in the presence of outliers …”
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Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning von Chen, Chun‐Teh, Gu, Grace X.

“… In recent years, machine learning (ML) techniques are seen to be promising tools to discover and design novel materials …”
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Soft and hard computation methods for estimation of the effective thermal conductivity of sands von Rizvi, Zarghaam Haider, Zaidi, Husain Haider, Akhtar, Syed Jawad, Sattari, Amir Shorian, Wuttke, Frank

“… Thermal properties of sand are of importance in numerous engineering and scientific applications ranging from energy storage and transportation infrastructures …”
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Enhanced remaining useful life prediction of lithium-ion batteries using genetic algorithm-optimized backpropagation neural networks von Li, Xiang, Du, Haozhe, Wang, Tian, Bi, Jing, Zhang, Haiyan, Zhao, Shu, Yu, Haijun

“… This study proposes a genetic algorithm (GA)-optimized backpropagation (BP) neural network that eliminates the need for complex feature engineering and improves convergence robustness …”
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Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training Algorithm von Zaidi, Imen, Chtourou, Mohamed, Djemel, Mohamed

“… In previous works, the neural models are trained classically by backpropagation (BP) algorithm. In this work, the sliding mode-backpropagation …”
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Quantitative Analysis of Major Metals in Agricultural Biochar Using Laser-Induced Breakdown Spectroscopy with an Adaboost Artificial Neural Network Algorithm von Duan, Hongwei, Han, Lujia, Huang, Guangqun

“… To promote the green development of agriculture by returning biochar to farmland, it is of great significance to simultaneously detect heavy and nutritional …”
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Enhanced backpropagation neural network accuracy through an improved genetic algorithm for tourist flow prediction in an ecological village von Chen, Xiaolong, Wong, Cora Un In, Zhang, Hongfeng, Song, Zhengchun

“… ) and Genetic Algorithm-Backpropagation Neural Network (GABP-NN). However, those models cannot well address the challenge of nonlinear complexity of tourists …”
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction von Hammid, Ali Thaeer, Sulaiman, Mohd Herwan Bin, Awad, Omar I.

“… The applications of backpropagation neural network (BPNN) are very various and saturated. The linear threshold part of the BPNN produces rapid learning with bounded abilities, also the procedure of BPNN causes the slow speed of training …”
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A New Correntropy-Based Conjugate Gradient Backpropagation Algorithm for Improving Training in Neural Networks von Heravi, Ahmad Reza, Abed Hodtani, Ghosheh

“… In this paper, we suggest a group of novel robust information theoretic backpropagation (BP) methods, as correntropy-based conjugate gradient BP (CCG-BP …”
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Backpropagation Algorithm and its Hardware Implementations: A Review von Kuninti, Shivani, Rooban, S

“… The combination of hardware and software modules help to build systems in a robust manner. This paper focuses mainly on back propagation algorithm and its different hardware implementation using FPGA, ASIC, Memristor and Microcontroller …”
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Maximal overlap discrete wavelet transform and deep learning for robust denoising and detection of power quality disturbance von Xiao, Fei, Lu, Tianguang, Wu, Mingli, Ai, Qian

“… The proposed PQ detection algorithm is robust even without a detection threshold and independent of the sampling frequency of PQ recording …”
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Learning in the machine: Recirculation is random backpropagation von Baldi, P., Sadowski, P.

“… Learning in physical neural systems must rely on learning rules that are local in both space and time …”
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Integrating convolutional layers and biformer network with forward-forward and backpropagation training von Kianfar, Ali, Razzaghi, Parvin, Asgari, Zahra

“… Our methodology combines convolutional neural networks (CNNs) with a BiFormer attention mechanism, employing both the forward-forward algorithm and backpropagation …”
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A comparison of quaternion neural network backpropagation algorithms von Bill, Jeremiah, Cox, Bruce A., Champagne, Lance

“… This work aims to unify existing research by evaluating four distinct QNN backpropagation algorithms, including the novel GHR-calculus backpropagation algorithm, and providing concise, scalable …”
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Data Value Assessment in Digital Economy Based on Backpropagation Neural Network Optimized by Genetic Algorithm von Qin, Xujiang, He, Qi, Zhang, Xin, Yang, Xiang

“… This growing importance necessitates accurate and robust valuation methods. Data valuation poses core modeling challenges due to its nonlinear nature and the instability …”
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