Artykuły w czasopismach na temat „Neural network RBF”
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Zhu, Jian Min, Peng Du i Ting Ting Fu. "Research for RBF Neural Networks Modeling Accuracy of Determining the Basis Function Center Based on Clustering Methods". Advanced Materials Research 317-319 (sierpień 2011): 1529–36. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.1529.
Pełny tekst źródłaLuan, Tiantian, Mingxiao Sun, Guoqing Xia i Daidai Chen. "Evaluation for Sortie Generation Capacity of the Carrier Aircraft Based on the Variable Structure RBF Neural Network with the Fast Learning Rate". Complexity 2018 (22.10.2018): 1–19. http://dx.doi.org/10.1155/2018/6950124.
Pełny tekst źródłaYakovyna, V. S. "Software failures prediction using RBF neural network". Odes’kyi Politechnichnyi Universytet. Pratsi, nr 2 (15.06.2015): 111–18. http://dx.doi.org/10.15276/opu.2.46.2015.20.
Pełny tekst źródłaWen, Hui, Tao Yan, Zhiqiang Liu i Deli Chen. "Integrated neural network model with pre-RBF kernels". Science Progress 104, nr 3 (lipiec 2021): 003685042110261. http://dx.doi.org/10.1177/00368504211026111.
Pełny tekst źródłaLiu, Yunbing. "Research on Nonlinear Time Series Processing Method for Automatic Building Construction Management". Journal of Control Science and Engineering 2022 (30.06.2022): 1–6. http://dx.doi.org/10.1155/2022/7025223.
Pełny tekst źródłaYu, Fa Hong, Mei Jia Chen i Wei Zhi Liao. "A Novel Learning Evaluation Method Based on RBF Neural Network". Applied Mechanics and Materials 385-386 (sierpień 2013): 1697–700. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.1697.
Pełny tekst źródłaLi, Hui Jun, i Li Zhang. "Prediction of Tensile Strength Based on RBF Neural Network". Advanced Materials Research 476-478 (luty 2012): 1309–12. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.1309.
Pełny tekst źródłaLiu, Dong Dong. "A Method about Load Distribution of Rolling Mills Based on RBF Neural Network". Advanced Materials Research 279 (lipiec 2011): 418–22. http://dx.doi.org/10.4028/www.scientific.net/amr.279.418.
Pełny tekst źródłaTsoulos, Ioannis G., Alexandros Tzallas i Evangelos Karvounis. "A Two-Phase Evolutionary Method to Train RBF Networks". Applied Sciences 12, nr 5 (25.02.2022): 2439. http://dx.doi.org/10.3390/app12052439.
Pełny tekst źródłaYu, Ying. "GDP Economic Forecasting Model Based on Improved RBF Neural Network". Mathematical Problems in Engineering 2022 (9.09.2022): 1–11. http://dx.doi.org/10.1155/2022/7630268.
Pełny tekst źródłaSchmitt, Michael. "Descartes' Rule of Signs for Radial Basis Function Neural Networks". Neural Computation 14, nr 12 (1.12.2002): 2997–3011. http://dx.doi.org/10.1162/089976602760805386.
Pełny tekst źródłaShymkovych, Volodymyr, Sergii Telenyk i Petro Kravets. "Hardware implementation of radial-basis neural networks with Gaussian activation functions on FPGA". Neural Computing and Applications 33, nr 15 (13.03.2021): 9467–79. http://dx.doi.org/10.1007/s00521-021-05706-3.
Pełny tekst źródłaMa, Lili, Jiangping Liu i Jidong Luo. "Method of Wireless Sensor Network Data Fusion". International Journal of Online Engineering (iJOE) 13, nr 09 (22.09.2017): 114. http://dx.doi.org/10.3991/ijoe.v13i09.7589.
Pełny tekst źródłaLiu, Li Long, Jun Yu Li, Chen Hui Cai i Guo Biao Lin. "Research on the GPS Elevation Fitting with RBF Neural Network Model Considering Effects of Sample Data Preprocessing". Applied Mechanics and Materials 568-570 (czerwiec 2014): 817–21. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.817.
Pełny tekst źródłaSheng, Zhong Biao, i Xiao Rong Tong. "The Application of RBF Neural Networks in Curve Fitting". Advanced Materials Research 490-495 (marzec 2012): 688–92. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.688.
Pełny tekst źródłaGan, Xu Sheng, i Hai Long Gao. "Research on Learning Algorithm of RBF Neural Network Based on Extended Kalman Filter". Advanced Materials Research 989-994 (lipiec 2014): 2705–8. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2705.
Pełny tekst źródłaBahita, Mohamed, i Khaled Belarbi. "Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator". Serbian Journal of Electrical Engineering 8, nr 3 (2011): 307–23. http://dx.doi.org/10.2298/sjee1103307b.
Pełny tekst źródłaSu, Hong Sheng. "Stream Turbine Vibration Fault Diagnosis". Applied Mechanics and Materials 340 (lipiec 2013): 90–94. http://dx.doi.org/10.4028/www.scientific.net/amm.340.90.
Pełny tekst źródłaChen, Tongqing, Lei Wang, Xijuan Jiang, Yubin Wang i Kai Yan. "Finite Element Model Modification of Arch Bridge Based on Radial Basis Function Neural Network". E3S Web of Conferences 136 (2019): 04033. http://dx.doi.org/10.1051/e3sconf/201913604033.
Pełny tekst źródłaZeng, Qing Wei, Zhi Hai Xu i Geng Sheng Deng. "Study on Dynamic Load Balance Method Based on Genetic Algorithm and RBF Neural Network". Advanced Materials Research 108-111 (maj 2010): 207–10. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.207.
Pełny tekst źródłaTang, Xiaowei, Bing Xu i Zichen Xu. "Reactor Temperature Prediction Method Based on CPSO-RBF-BP Neural Network". Applied Sciences 13, nr 5 (2.03.2023): 3230. http://dx.doi.org/10.3390/app13053230.
Pełny tekst źródła张, 轶. "Option Pricing with BP Neural Network and RBF Neural Network". Statistical and Application 02, nr 04 (2013): 119–26. http://dx.doi.org/10.12677/sa.2013.24018.
Pełny tekst źródłaLeow, Shoun Ying, Keem Siah Yap i Shen Yuong Wong. "Harmonic current classification using hybrid FAM-RBF neural network". Indonesian Journal of Electrical Engineering and Computer Science 18, nr 3 (1.06.2020): 1551. http://dx.doi.org/10.11591/ijeecs.v18.i3.pp1551-1558.
Pełny tekst źródłaLv, Bailin, i Yizhang Jiang. "Prediction of Short-Term Stock Price Trend Based on Multiview RBF Neural Network". Computational Intelligence and Neuroscience 2021 (28.11.2021): 1–13. http://dx.doi.org/10.1155/2021/8495288.
Pełny tekst źródłaWang, Wu, i Zheng Yin Zhao. "Application of Adaptive RBF-SMC for Electro-Hydraulic Position Servo System". Advanced Materials Research 463-464 (luty 2012): 1440–44. http://dx.doi.org/10.4028/www.scientific.net/amr.463-464.1440.
Pełny tekst źródłaXiao, Lijun, i Yan Luo. "The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching". Computational Intelligence and Neuroscience 2022 (13.06.2022): 1–9. http://dx.doi.org/10.1155/2022/4206857.
Pełny tekst źródłaLee, N. K., i D. Wang. "Realization of Generalized RBF Network". Journal of IT in Asia 1, nr 1 (21.07.2017): 1–16. http://dx.doi.org/10.33736/jita.400.2005.
Pełny tekst źródłaWu, Hong Qi, i Xiao Bin Li. "Research on Intelligent Diagnosis Technology of Transformer Fault". Applied Mechanics and Materials 385-386 (sierpień 2013): 589–92. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.589.
Pełny tekst źródłaDawson, C. W., C. Harpham, R. L. Wilby i Y. Chen. "Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China". Hydrology and Earth System Sciences 6, nr 4 (31.08.2002): 619–26. http://dx.doi.org/10.5194/hess-6-619-2002.
Pełny tekst źródłaXie, Xiao Zhu, i Xing Lai Guan. "A Novel Control Scheme Based on Improved RBF Neural Network". Applied Mechanics and Materials 182-183 (czerwiec 2012): 1313–17. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1313.
Pełny tekst źródłaHu, Peitao, i Liu Changliang. "Soft-sensing of NOx content in power Station based on BP Neural Network, RBF Neural Network and PCA-RBF Neural Network". IOP Conference Series: Materials Science and Engineering 392, nr 6 (3.08.2018): 062180. http://dx.doi.org/10.1088/1757-899x/392/6/062180.
Pełny tekst źródłaDing, Shuo, Xiao Heng Chang i Qing Hui Wu. "Fault Diagnosis of Induction Motors Based on RBF Neural Network". Applied Mechanics and Materials 462-463 (listopad 2013): 85–88. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.85.
Pełny tekst źródłaYu, Cheng Bo, Jun Tan, Lei Yu i Yin Li Tian. "A Finger Vein Recognition Method Based on PCA-RBF Neural Network". Applied Mechanics and Materials 325-326 (czerwiec 2013): 1653–58. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1653.
Pełny tekst źródłaLiu, Wei, Feifan Wang, Xiawei Yang i Wenya Li. "Upset Prediction in Friction Welding Using Radial Basis Function Neural Network". Advances in Materials Science and Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/196382.
Pełny tekst źródłaLiu, Xi Mei, Xiao Hui Yao, Qian Zhao i Hong Mi Guo. "Application of RBF Neural Network in Fault Diagnosis for Transmission Gear". Advanced Materials Research 433-440 (styczeń 2012): 7563–68. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.7563.
Pełny tekst źródłaYu, Meixia, Xiaoping Zheng i Chuanhui Zhao. "Research on the Prediction Method of Clock Tester Calibration Data Based on Radial Basis Function Neural Network". Electronics 12, nr 22 (17.11.2023): 4677. http://dx.doi.org/10.3390/electronics12224677.
Pełny tekst źródłaHuang, Yifan, Ziwei Xiong, Yubin Zhao, Wei Wang i Xingming Xu. "Mid-long-term prediction of electrical load based on particle swarm optimization and RBF neural network". Journal of Physics: Conference Series 2355, nr 1 (1.10.2022): 012049. http://dx.doi.org/10.1088/1742-6596/2355/1/012049.
Pełny tekst źródłaYin, Rongwang, Qingyu Li, Peichao Li i Detang Lu. "Parameter Identification of Multistage Fracturing Horizontal Well Based on PSO-RBF Neural Network". Scientific Programming 2020 (3.07.2020): 1–11. http://dx.doi.org/10.1155/2020/6810903.
Pełny tekst źródłaLi, Yong Wei, Zhi Gang Ye i Chao Chao Huo. "The Method Research of Grey Neural Network Control Based on Data". Applied Mechanics and Materials 602-605 (sierpień 2014): 1131–34. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1131.
Pełny tekst źródłaSoper, Daniel S. "Using an Opportunity Matrix to Select Centers for RBF Neural Networks". Algorithms 16, nr 10 (23.09.2023): 455. http://dx.doi.org/10.3390/a16100455.
Pełny tekst źródłaTan, Yun Liang, i Ze Zhang. "A RBF Neural Network Approach for Fitting Creep Curve of Sandstone". Advanced Materials Research 171-172 (grudzień 2010): 274–77. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.274.
Pełny tekst źródłaZhang, Meifeng, Yongxin Li, Jianwen Cai, Fuhao Chen i Xin Miao. "Research on fault diagnosis of diesel engine based on PCA-RBF neural network". Modern Physics Letters B 32, nr 34n36 (30.12.2018): 1840099. http://dx.doi.org/10.1142/s0217984918400997.
Pełny tekst źródłaFang, Yu, Zheng Wei Chang, Hao Wu i Xian Feng Tang. "Identification the Faulty Components in Power Networks Based on Wide Area Information and RBF Neural Network". Applied Mechanics and Materials 568-570 (czerwiec 2014): 842–47. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.842.
Pełny tekst źródłaYang, Yongkang, Qiaoyi Du, Chenlong Wang i Yu Bai. "Research on the Method of Methane Emission Prediction Using Improved Grey Radial Basis Function Neural Network Model". Energies 13, nr 22 (21.11.2020): 6112. http://dx.doi.org/10.3390/en13226112.
Pełny tekst źródłaYang, Qin, Zhaofa Ye, Xuzheng Li, Daozhu Wei, Shunhua Chen i Zhirui Li. "Prediction of Flight Status of Logistics UAVs Based on an Information Entropy Radial Basis Function Neural Network". Sensors 21, nr 11 (24.05.2021): 3651. http://dx.doi.org/10.3390/s21113651.
Pełny tekst źródłaZhang, Liu. "Research of Automotive Glass Fog System Based on RBF Neural Network". Advanced Materials Research 588-589 (listopad 2012): 1441–45. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1441.
Pełny tekst źródłaChen, Dong. "Evaluation Model of Physical Education Effect: On the Application of Radial Basis Function-Particle Swarm Optimization Neural Network (RBFNN-PSO)". Computational Intelligence and Neuroscience 2021 (30.07.2021): 1–11. http://dx.doi.org/10.1155/2021/6819493.
Pełny tekst źródłaChang, Wen Yeau. "State of Charge Estimation for LFP Battery Using the Hybrid Method". Applied Mechanics and Materials 431 (październik 2013): 221–25. http://dx.doi.org/10.4028/www.scientific.net/amm.431.221.
Pełny tekst źródłaNedbalek, Jakub. "Rbf Neural Networks for Function Approximation in Dynamic Modelling". Journal of Konbin 8, nr 1 (1.01.2008): 223–32. http://dx.doi.org/10.2478/v10040-008-0115-6.
Pełny tekst źródłaWilkins, M. F., Lynne Boddy, C. W. Morris i R. R. Jonker. "Identification of Phytoplankton from Flow Cytometry Data by Using Radial Basis Function Neural Networks". Applied and Environmental Microbiology 65, nr 10 (1.10.1999): 4404–10. http://dx.doi.org/10.1128/aem.65.10.4404-4410.1999.
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