Статті в журналах з теми "EMD - Neural networks"
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Zheng, Jing Wen, Shi Xiao Li, and Yang Kun. "A New Hybrid Model for Forecasting Crude Oil Price and the Techniques in the Model." Advanced Materials Research 974 (June 2014): 310–17. http://dx.doi.org/10.4028/www.scientific.net/amr.974.310.
Повний текст джерелаSaâdaoui, Foued, and Othman Ben Messaoud. "Multiscaled Neural Autoregressive Distributed Lag: A New Empirical Mode Decomposition Model for Nonlinear Time Series Forecasting." International Journal of Neural Systems 30, no. 08 (June 26, 2020): 2050039. http://dx.doi.org/10.1142/s0129065720500392.
Повний текст джерелаLei, Yu, Danning Zhao, and Hongbing Cai. "Ultra Short-term Prediction of Pole Coordinates via Combination of Empirical Mode Decomposition and Neural Networks." Artificial Satellites 51, no. 4 (December 1, 2016): 149–61. http://dx.doi.org/10.1515/arsa-2016-0013.
Повний текст джерелаGe, Yujia, Yurong Nan, and Lijun Bai. "A Hybrid Prediction Model for Solar Radiation Based on Long Short-Term Memory, Empirical Mode Decomposition, and Solar Profiles for Energy Harvesting Wireless Sensor Networks." Energies 12, no. 24 (December 13, 2019): 4762. http://dx.doi.org/10.3390/en12244762.
Повний текст джерелаJiang, Qi, Yuxin Cheng, Haozhe Le, Chunquan Li, and Peter X. Liu. "A Stacking Learning Model Based on Multiple Similar Days for Short-Term Load Forecasting." Mathematics 10, no. 14 (July 13, 2022): 2446. http://dx.doi.org/10.3390/math10142446.
Повний текст джерелаHuang, Xiaoxin, and Xiuxiu Chen. "A Quantitative Model of International Trade Based on Deep Neural Network." Computational Intelligence and Neuroscience 2022 (May 31, 2022): 1–11. http://dx.doi.org/10.1155/2022/9811358.
Повний текст джерелаZhou, Shuyi, Brandon J. Bethel, Wenjin Sun, Yang Zhao, Wenhong Xie, and Changming Dong. "Improving Significant Wave Height Forecasts Using a Joint Empirical Mode Decomposition–Long Short-Term Memory Network." Journal of Marine Science and Engineering 9, no. 7 (July 5, 2021): 744. http://dx.doi.org/10.3390/jmse9070744.
Повний текст джерелаZhang, Boning. "Foreign exchange rates forecasting with an EMD-LSTM neural networks model." Journal of Physics: Conference Series 1053 (July 2018): 012005. http://dx.doi.org/10.1088/1742-6596/1053/1/012005.
Повний текст джерелаChengzhao, Zhang, Pan Heiping, and Zhou Ke. "Comparison of Back Propagation Neural Networks and EMD-Based Neural Networks in Forecasting the Three Major Asian Stock Markets." Journal of Applied Sciences 15, no. 1 (December 15, 2014): 90–99. http://dx.doi.org/10.3923/jas.2015.90.99.
Повний текст джерелаShu, Wangwei, and Qiang Gao. "Forecasting Stock Price Based on Frequency Components by EMD and Neural Networks." IEEE Access 8 (2020): 206388–95. http://dx.doi.org/10.1109/access.2020.3037681.
Повний текст джерелаTeng, Xian Bin, Jun Dong Zhang, Shi Hai Zhang, and Ran Ran Wang. "Fault Diagnosis of Diesel Engine Based on Wavelet Analysis, EMD and Neural Networks." Advanced Materials Research 211-212 (February 2011): 1031–35. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.1031.
Повний текст джерелаMEHBOOB, ZAREEN, and HUJUN YIN. "INFORMATION QUANTIFICATION OF EMPIRICAL MODE DECOMPOSITION AND APPLICATIONS TO FIELD POTENTIALS." International Journal of Neural Systems 21, no. 01 (February 2011): 49–63. http://dx.doi.org/10.1142/s012906571100264x.
Повний текст джерелаLin, Hualing, and Qiubi Sun. "Crude Oil Prices Forecasting: An Approach of Using CEEMDAN-Based Multi-Layer Gated Recurrent Unit Networks." Energies 13, no. 7 (March 25, 2020): 1543. http://dx.doi.org/10.3390/en13071543.
Повний текст джерелаGui, Sibo, Meng Shi, Zhaolong Li, Haitao Wu, Quansheng Ren, and Jianye Zhao. "A Deep-Learning-Based Method for Optical Transmission Link Assessment Applied to Optical Clock Comparisons." Photonics 10, no. 8 (August 10, 2023): 920. http://dx.doi.org/10.3390/photonics10080920.
Повний текст джерелаHassard, Alan. "Investigaton of Eye Movement Desensitization in Pain Clinic Patients." Behavioural and Cognitive Psychotherapy 23, no. 2 (April 1995): 177–85. http://dx.doi.org/10.1017/s1352465800014429.
Повний текст джерелаHU, Niaoqing. "Fault Diagnosis for Planetary Gearbox Based on EMD and Deep Convolutional Neural Networks." Journal of Mechanical Engineering 55, no. 7 (2019): 9. http://dx.doi.org/10.3901/jme.2019.07.009.
Повний текст джерелаCarmona, A. M., and G. Poveda. "Prediction of mean monthly river discharges in Colombia through Empirical Mode Decomposition." Proceedings of the International Association of Hydrological Sciences 366 (April 10, 2015): 172. http://dx.doi.org/10.5194/piahs-366-172-2015.
Повний текст джерелаLi, Chao, Quanjie Guo, Lei Shao, Ji Li, and Han Wu. "Research on Short-Term Load Forecasting Based on Optimized GRU Neural Network." Electronics 11, no. 22 (November 21, 2022): 3834. http://dx.doi.org/10.3390/electronics11223834.
Повний текст джерелаCenteno-Bautista, Manuel A., Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, Juan P. Amezquita-Sanchez, David Granados-Lieberman, and Martin Valtierra-Rodriguez. "Electrocardiogram Analysis by Means of Empirical Mode Decomposition-Based Methods and Convolutional Neural Networks for Sudden Cardiac Death Detection." Applied Sciences 13, no. 6 (March 10, 2023): 3569. http://dx.doi.org/10.3390/app13063569.
Повний текст джерелаWu, Jian Hua, Zheng Qiang Yao, Y. Jin, H. B. Xie, Y. S. Zhao, and L. Ch Xu. "Application of Hilbert-Huang Transform to Predict Grinding Surface Quality On-Line." Key Engineering Materials 304-305 (February 2006): 227–31. http://dx.doi.org/10.4028/www.scientific.net/kem.304-305.227.
Повний текст джерелаMbatha, Nkanyiso, and Hassan Bencherif. "Time Series Analysis and Forecasting Using a Novel Hybrid LSTM Data-Driven Model Based on Empirical Wavelet Transform Applied to Total Column of Ozone at Buenos Aires, Argentina (1966–2017)." Atmosphere 11, no. 5 (April 30, 2020): 457. http://dx.doi.org/10.3390/atmos11050457.
Повний текст джерелаWang, Yijun, Peiqian Guo, Nan Ma, and Guowei Liu. "Robust Wavelet Transform Neural-Network-Based Short-Term Load Forecasting for Power Distribution Networks." Sustainability 15, no. 1 (December 24, 2022): 296. http://dx.doi.org/10.3390/su15010296.
Повний текст джерелаFeng, Zhijie, Po Hu, Shuiqing Li, and Dongxue Mo. "Prediction of Significant Wave Height in Offshore China Based on the Machine Learning Method." Journal of Marine Science and Engineering 10, no. 6 (June 20, 2022): 836. http://dx.doi.org/10.3390/jmse10060836.
Повний текст джерелаAhmed, Ammar, Youssef Serrestou, Kosai Raoof, and Jean-François Diouris. "Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification." Sensors 22, no. 20 (October 11, 2022): 7717. http://dx.doi.org/10.3390/s22207717.
Повний текст джерелаPopa, Stefan Lucian, Teodora Surdea-Blaga, Dan Lucian Dumitrascu, Giuseppe Chiarioni, Edoardo Savarino, Liliana David, Abdulrahman Ismaiel, et al. "Automatic Diagnosis of High-Resolution Esophageal Manometry Using Artificial Intelligence." Journal of Gastrointestinal and Liver Diseases 31, no. 4 (December 16, 2022): 383–89. http://dx.doi.org/10.15403/jgld-4525.
Повний текст джерелаDryuchenko, M. A., and A. A. Sirota. "Image stegoanalysis using deep neural networks and heteroassociative integral transformations." Prikladnaya Diskretnaya Matematika, no. 55 (2022): 35–58. http://dx.doi.org/10.17223/20710410/55/3.
Повний текст джерелаJiao, Xiaoxuan, Bo Jing, Yifeng Huang, Juan Li, and Guangyue Xu. "Research on fault diagnosis of airborne fuel pump based on EMD and probabilistic neural networks." Microelectronics Reliability 75 (August 2017): 296–308. http://dx.doi.org/10.1016/j.microrel.2017.03.007.
Повний текст джерелаLiu, Die, Yihao Bao, Yingying He, and Likai Zhang. "A Data Loss Recovery Technique Using EMD-BiGRU Algorithm for Structural Health Monitoring." Applied Sciences 11, no. 21 (October 27, 2021): 10072. http://dx.doi.org/10.3390/app112110072.
Повний текст джерелаKang, Aiqing, Qingxiong Tan, Xiaohui Yuan, Xiaohui Lei, and Yanbin Yuan. "Short-Term Wind Speed Prediction Using EEMD-LSSVM Model." Advances in Meteorology 2017 (2017): 1–22. http://dx.doi.org/10.1155/2017/6856139.
Повний текст джерелаMa, Yu. "Two models for predicting stock prices in combination with LSTM." Highlights in Business, Economics and Management 5 (February 16, 2023): 664–73. http://dx.doi.org/10.54097/hbem.v5i.5256.
Повний текст джерелаYu, Jing, Feng Ding, Chenghao Guo, and Yabin Wang. "System load trend prediction method based on IF-EMD-LSTM." International Journal of Distributed Sensor Networks 15, no. 8 (August 2019): 155014771986765. http://dx.doi.org/10.1177/1550147719867655.
Повний текст джерелаGuerrero-Sánchez, Alma E., Edgar A. Rivas-Araiza, Mariano Garduño-Aparicio, Saul Tovar-Arriaga, Juvenal Rodriguez-Resendiz, and Manuel Toledano-Ayala. "A Novel Methodology for Classifying Electrical Disturbances Using Deep Neural Networks." Technologies 11, no. 4 (June 21, 2023): 82. http://dx.doi.org/10.3390/technologies11040082.
Повний текст джерелаCao, Zhiyong, Zhijuan Cao, Hongwei Zhao, Jiajun Xu, Guangyong Zhang, Yi Li, Yufei Su, Ling Lou, Xiujuan Yang, and Zhaobing Gu. "Using Empirical Modal Decomposition to Improve the Daily Milk Yield Prediction of Cows." Wireless Communications and Mobile Computing 2022 (July 11, 2022): 1–7. http://dx.doi.org/10.1155/2022/1685841.
Повний текст джерелаSadrawi, Muammar, Shou-Zen Fan, Maysam F. Abbod, Kuo-Kuang Jen, and Jiann-Shing Shieh. "Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks." BioMed Research International 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/536863.
Повний текст джерелаJin, Zebin, Yixiao Jin, and Zhiyun Chen. "Empirical mode decomposition using deep learning model for financial market forecasting." PeerJ Computer Science 8 (September 14, 2022): e1076. http://dx.doi.org/10.7717/peerj-cs.1076.
Повний текст джерелаRedwan, Sadi M., Md Rashed-Al-Mahfuz, and Md Ekramul Hamid. "Recognizing Command Words using Deep Recurrent Neural Network for Both Acoustic and Throat Speech." European Journal of Information Technologies and Computer Science 3, no. 2 (May 22, 2023): 7–13. http://dx.doi.org/10.24018/compute.2023.3.2.88.
Повний текст джерелаCamarena-Martinez, David, Martin Valtierra-Rodriguez, Arturo Garcia-Perez, Roque Alfredo Osornio-Rios, and Rene de Jesus Romero-Troncoso. "Empirical Mode Decomposition and Neural Networks on FPGA for Fault Diagnosis in Induction Motors." Scientific World Journal 2014 (2014): 1–17. http://dx.doi.org/10.1155/2014/908140.
Повний текст джерелаZheng, Huiting, Jiabin Yuan, and Long Chen. "Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation." Energies 10, no. 8 (August 8, 2017): 1168. http://dx.doi.org/10.3390/en10081168.
Повний текст джерелаXu, Da-Chuan, Huai-Shu Hou, Cai-Xia Liu, and Chao-Fei Jiao. "Defect type identification of thin-walled stainless steel seamless pipe based on eddy current testing." Insight - Non-Destructive Testing and Condition Monitoring 63, no. 12 (December 1, 2021): 697–703. http://dx.doi.org/10.1784/insi.2021.63.12.697.
Повний текст джерелаRofii, Faqih, Agus Naba, Hari Arief Dharmawan, and Fachrudin Hunaini. "Development of empirical mode decomposition based neural network for power quality disturbances classification." EUREKA: Physics and Engineering, no. 2 (March 31, 2022): 28–44. http://dx.doi.org/10.21303/2461-4262.2022.002046.
Повний текст джерелаAltuve, Miguel, Paula Lizarazo, and Javier Villamizar. "Human activity recognition using improved complete ensemble EMD with adaptive noise and long short-term memory neural networks." Biocybernetics and Biomedical Engineering 40, no. 3 (July 2020): 901–9. http://dx.doi.org/10.1016/j.bbe.2020.04.007.
Повний текст джерелаAsghar, Muhammad Adeel, Muhammad Jamil Khan, Muhammad Rizwan, Raja Majid Mehmood, and Sun-Hee Kim. "An Innovative Multi-Model Neural Network Approach for Feature Selection in Emotion Recognition Using Deep Feature Clustering." Sensors 20, no. 13 (July 5, 2020): 3765. http://dx.doi.org/10.3390/s20133765.
Повний текст джерелаWang, Dongyu, Xiwen Cui, and Dongxiao Niu. "Wind Power Forecasting Based on LSTM Improved by EMD-PCA-RF." Sustainability 14, no. 12 (June 15, 2022): 7307. http://dx.doi.org/10.3390/su14127307.
Повний текст джерелаGao, Hongbo, Shuang Qiu, Jun Fang, Nan Ma, Jiye Wang, Kun Cheng, Hui Wang, et al. "Short-Term Prediction of PV Power Based on Combined Modal Decomposition and NARX-LSTM-LightGBM." Sustainability 15, no. 10 (May 18, 2023): 8266. http://dx.doi.org/10.3390/su15108266.
Повний текст джерелаDiez, Pablo F., Vicente A. Mut, Eric Laciar, Abel Torres, and Enrique M. Avila Perona. "FEATURES EXTRACTION METHOD FOR BRAIN-MACHINE COMMUNICATION BASED ON THE EMPIRICAL MODE DECOMPOSITION." Biomedical Engineering: Applications, Basis and Communications 25, no. 06 (December 2013): 1350058. http://dx.doi.org/10.4015/s1016237213500580.
Повний текст джерелаJaramillo-Morán, Miguel A., Daniel Fernández-Martínez, Agustín García-García, and Diego Carmona-Fernández. "Improving Artificial Intelligence Forecasting Models Performance with Data Preprocessing: European Union Allowance Prices Case Study." Energies 14, no. 23 (November 23, 2021): 7845. http://dx.doi.org/10.3390/en14237845.
Повний текст джерелаZeng, Wei, Mengqing Li, Chengzhi Yuan, Qinghui Wang, Fenglin Liu, and Ying Wang. "Classification of focal and non focal EEG signals using empirical mode decomposition (EMD), phase space reconstruction (PSR) and neural networks." Artificial Intelligence Review 52, no. 1 (April 3, 2019): 625–47. http://dx.doi.org/10.1007/s10462-019-09698-4.
Повний текст джерелаMohsenimanesh, Ahmad, Evgueniy Entchev, and Filip Bosnjak. "Hybrid Model Based on an SD Selection, CEEMDAN, and Deep Learning for Short-Term Load Forecasting of an Electric Vehicle Fleet." Applied Sciences 12, no. 18 (September 16, 2022): 9288. http://dx.doi.org/10.3390/app12189288.
Повний текст джерелаDang, Sanlei, Long Peng, Jingming Zhao, Jiajie Li, and Zhengmin Kong. "A Quantile Regression Random Forest-Based Short-Term Load Probabilistic Forecasting Method." Energies 15, no. 2 (January 17, 2022): 663. http://dx.doi.org/10.3390/en15020663.
Повний текст джерелаZhang, Yixiang, Zenggui Gao, Jiachen Sun, and Lilan Liu. "Machine-Learning Algorithms for Process Condition Data-Based Inclusion Prediction in Continuous-Casting Process: A Case Study." Sensors 23, no. 15 (July 27, 2023): 6719. http://dx.doi.org/10.3390/s23156719.
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