Artigos de revistas sobre o tema "DBN (Deep Belief Network)"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Veja os 50 melhores artigos de revistas para estudos sobre o assunto "DBN (Deep Belief Network)".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Veja os artigos de revistas das mais diversas áreas científicas e compile uma bibliografia correta.
Peng, Fan, Suping Peng, Wenfeng Du e Hongshuan Liu. "Coalbed methane content prediction using deep belief network". Interpretation 8, n.º 2 (1 de maio de 2020): T309—T321. http://dx.doi.org/10.1190/int-2019-0126.1.
Texto completo da fonteZhang, Kaiyu, Shanshan Shi, Shu Liu, Junjie Wan e Lijia Ren. "Research on DBN-based Evaluation of Distribution Network Reliability". E3S Web of Conferences 242 (2021): 03004. http://dx.doi.org/10.1051/e3sconf/202124203004.
Texto completo da fonteYang, Lei, Chunqing Zhao, Chao Lu, Lianzhen Wei e Jianwei Gong. "Lateral and Longitudinal Driving Behavior Prediction Based on Improved Deep Belief Network". Sensors 21, n.º 24 (20 de dezembro de 2021): 8498. http://dx.doi.org/10.3390/s21248498.
Texto completo da fonteSun, Lili. "Optimization of Physical Education Course Resource Allocation Model Based on Deep Belief Network". Mathematical Problems in Engineering 2023 (29 de abril de 2023): 1–8. http://dx.doi.org/10.1155/2023/8457760.
Texto completo da fontePrabowo, Abram Setyo, Agus Sihabuddin e Azhari SN. "Adaptive Moment Estimation On Deep Belief Network For Rupiah Currency Forecasting". IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 13, n.º 1 (31 de janeiro de 2019): 31. http://dx.doi.org/10.22146/ijccs.39071.
Texto completo da fonteTan, Xiaopeng, Shaojing Su, Zhen Zuo, Xiaojun Guo e Xiaoyong Sun. "Intrusion Detection of UAVs Based on the Deep Belief Network Optimized by PSO". Sensors 19, n.º 24 (14 de dezembro de 2019): 5529. http://dx.doi.org/10.3390/s19245529.
Texto completo da fonteYan, Yan, Xu-Cheng Yin, Sujian Li, Mingyuan Yang e Hong-Wei Hao. "Learning Document Semantic Representation with Hybrid Deep Belief Network". Computational Intelligence and Neuroscience 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/650527.
Texto completo da fonteYang, Huihua, Baichao Hu, Xipeng Pan, Shengke Yan, Yanchun Feng, Xuebo Zhang, Lihui Yin e Changqin Hu. "Deep belief network-based drug identification using near infrared spectroscopy". Journal of Innovative Optical Health Sciences 10, n.º 02 (março de 2017): 1630011. http://dx.doi.org/10.1142/s1793545816300111.
Texto completo da fonteSharipuddin, Sharipuddin, Eko Arip Winanto, Zulwaqar Zain Mohtar, Kurniabudi Kurniabudi, Ibnu Sani Wijaya e Dodi Sandra. "Improvement detection system on complex network using hybrid deep belief network and selection features". Indonesian Journal of Electrical Engineering and Computer Science 31, n.º 1 (1 de julho de 2023): 470. http://dx.doi.org/10.11591/ijeecs.v31.i1.pp470-479.
Texto completo da fonteAnh, Duong Tuan, e Ta Ngoc Huy Nam. "Chaotic time series prediction with deep belief networks: an empirical evaluation". Science & Technology Development Journal - Engineering and Technology 3, SI1 (4 de dezembro de 2020): SI102—SI112. http://dx.doi.org/10.32508/stdjet.v3isi1.571.
Texto completo da fonteRajadnya, Prof Kirti. "Speech Recognition using Deep Neural Network Neural (DNN) and Deep Belief Network (DBN)". International Journal for Research in Applied Science and Engineering Technology 8, n.º 5 (31 de maio de 2020): 1543–48. http://dx.doi.org/10.22214/ijraset.2020.5359.
Texto completo da fonteTong, Guiying. "Music Emotion Classification Method Using Improved Deep Belief Network". Mobile Information Systems 2022 (18 de março de 2022): 1–7. http://dx.doi.org/10.1155/2022/2715765.
Texto completo da fonteAlom, Zahangir, Venkata Ramesh Bontupalli e Tarek M. Taha. "Intrusion Detection Using Deep Belief Network and Extreme Learning Machine". International Journal of Monitoring and Surveillance Technologies Research 3, n.º 2 (abril de 2015): 35–56. http://dx.doi.org/10.4018/ijmstr.2015040103.
Texto completo da fonteZulfa, Ira, e Edi Winarko. "Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network". IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 11, n.º 2 (31 de julho de 2017): 187. http://dx.doi.org/10.22146/ijccs.24716.
Texto completo da fonteLi, Chenming, Yongchang Wang, Xiaoke Zhang, Hongmin Gao, Yao Yang e Jiawei Wang. "Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data". Sensors 19, n.º 1 (8 de janeiro de 2019): 204. http://dx.doi.org/10.3390/s19010204.
Texto completo da fonteArum, Aprilisa, e Pramono Pramono. "Penerapan Algoritma Deep Belief Networks (DBNs) Untuk Prediksi Kanker Serviks". DutaCom 17, n.º 1 (28 de fevereiro de 2023): 50–57. http://dx.doi.org/10.47701/dutacom.v17i1.3790.
Texto completo da fonteConstantin Menteng, Arief Setyanto e Hanif Al Fatta. "MODEL DETEKSI SERANGAN SSH-BRUTE FORCE BERDASARKAN DEEP BELIEF NETWORK". Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika 7, n.º 2 (5 de agosto de 2023): 101–10. http://dx.doi.org/10.47111/jti.v7i2.8151.
Texto completo da fonteJiang, Keruo, Zhen Huang, Xinyan Zhou, Chudong Tong, Minjie Zhu e Heshan Wang. "Deep belief improved bidirectional LSTM for multivariate time series forecasting". Mathematical Biosciences and Engineering 20, n.º 9 (2023): 16596–627. http://dx.doi.org/10.3934/mbe.2023739.
Texto completo da fonteRuiz Cárdenas, Luis Carlos, Dario Amaya Hurtado e Robinson Jiménez Moreno. "Predicción de radiación solar mediante deep belief network". Revista Tecnura 20, n.º 47 (18 de fevereiro de 2016): 39. http://dx.doi.org/10.14483/udistrital.jour.tecnura.2016.1.a03.
Texto completo da fonteZhong, P., Z. Q. Gong e C. Schönlieb. "A DIVERSIFIED DEEP BELIEF NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21 de junho de 2016): 443–49. http://dx.doi.org/10.5194/isprs-archives-xli-b7-443-2016.
Texto completo da fonteZhong, P., Z. Q. Gong e C. Schönlieb. "A DIVERSIFIED DEEP BELIEF NETWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21 de junho de 2016): 443–49. http://dx.doi.org/10.5194/isprsarchives-xli-b7-443-2016.
Texto completo da fonteWang, Shuqin, Gang Hua, Guosheng Hao e Chunli Xie. "A Cycle Deep Belief Network Model for Multivariate Time Series Classification". Mathematical Problems in Engineering 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/9549323.
Texto completo da fonteWang, Hai, Yingfeng Cai e Long Chen. "A Vehicle Detection Algorithm Based on Deep Belief Network". Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/647380.
Texto completo da fonteGourisaria, Mahendra Kumar, Harshvardhan GM, Rakshit Agrawal, Sudhansu Shekhar Patra, Siddharth Swarup Rautaray e Manjusha Pandey. "Arrhythmia Detection Using Deep Belief Network Extracted Features From ECG Signals". International Journal of E-Health and Medical Communications 12, n.º 6 (novembro de 2021): 1–24. http://dx.doi.org/10.4018/ijehmc.20211101.oa9.
Texto completo da fonteZhang, Yue, e Fangai Liu. "An Improved Deep Belief Network Prediction Model Based on Knowledge Transfer". Future Internet 12, n.º 11 (29 de outubro de 2020): 188. http://dx.doi.org/10.3390/fi12110188.
Texto completo da fonteXi, Shuyue, e Xiaozhong Xu. "Dynamic gaussian deep belief network design and stock market application". Intelligent Data Analysis 27, n.º 2 (15 de março de 2023): 519–34. http://dx.doi.org/10.3233/ida-216340.
Texto completo da fonteYang, Jianjian, Boshen Chang, Xiaolin Wang, Qiang Zhang, Chao Wang, Fan Wang e Miao Wu. "Design and Application of Deep Belief Network Based on Stochastic Adaptive Particle Swarm Optimization". Mathematical Problems in Engineering 2020 (24 de agosto de 2020): 1–10. http://dx.doi.org/10.1155/2020/6590765.
Texto completo da fonteShen, Changqing, Jiaqi Xie, Dong Wang, Xingxing Jiang, Juanjuan Shi e Zhongkui Zhu. "Improved Hierarchical Adaptive Deep Belief Network for Bearing Fault Diagnosis". Applied Sciences 9, n.º 16 (16 de agosto de 2019): 3374. http://dx.doi.org/10.3390/app9163374.
Texto completo da fonteSrinivasa Rao, T. C., S. S. Tulasi Ram e J. B. V. Subrahmanyam. "Fault Signal Recognition in Power Distribution System using Deep Belief Network". Journal of Intelligent Systems 29, n.º 1 (13 de março de 2018): 459–74. http://dx.doi.org/10.1515/jisys-2017-0499.
Texto completo da fonteM., Arshey, e Angel Viji K. S. "An optimization-based deep belief network for the detection of phishing e-mails". Data Technologies and Applications 54, n.º 4 (16 de julho de 2020): 529–49. http://dx.doi.org/10.1108/dta-02-2020-0043.
Texto completo da fonteSheng, Dali, Jinlian Deng, Wei Zhang, Jie Cai, Weisheng Zhao e Jiawei Xiang. "A Statistical Image Feature-Based Deep Belief Network for Fire Detection". Complexity 2021 (5 de agosto de 2021): 1–12. http://dx.doi.org/10.1155/2021/5554316.
Texto completo da fonteKadam, Vinod Jagannath, e Shivajirao Manikrao Jadhav. "Optimal weighted feature vector and deep belief network for medical data classification". International Journal of Wavelets, Multiresolution and Information Processing 18, n.º 02 (3 de dezembro de 2019): 2050006. http://dx.doi.org/10.1142/s021969132050006x.
Texto completo da fonteMunish, Saran, Kumar Yadav Rajan, Maurya Pranjal, Devi Sangeeta e Nath Tripathi Upendra. "A novel methodology for enhancing intrusion detection system". i-manager’s Journal on Software Engineering 17, n.º 4 (2023): 9. http://dx.doi.org/10.26634/jse.17.4.20009.
Texto completo da fonteKamada, Shin, Takumi Ichimura e Toshihide Harada. "Knowledge Extraction of Adaptive Structural Learning of Deep Belief Network for Medical Examination Data". International Journal of Semantic Computing 13, n.º 01 (março de 2019): 67–86. http://dx.doi.org/10.1142/s1793351x1940004x.
Texto completo da fonteXiao-Hong Qiu, Xiao-Hong Qiu, Jia-Li Chen Xiao-Hong Qiu e Zi-Ying Ao Jia-Li Chen. "Stall Warning Algorithm of Axial Compressor Based on SSA-DBN". 電腦學刊 33, n.º 3 (junho de 2022): 059–71. http://dx.doi.org/10.53106/199115992022063303005.
Texto completo da fonteZhao, Huimin, Xiaoxu Yang, Baojie Chen, Huayue Chen e Wu Deng. "Bearing fault diagnosis using transfer learning and optimized deep belief network". Measurement Science and Technology 33, n.º 6 (7 de março de 2022): 065009. http://dx.doi.org/10.1088/1361-6501/ac543a.
Texto completo da fonteLuu, Do Ngoc, Nguyen Ngoc Phien e Duong Tuan Anh. "Tuning Parameters in Deep Belief Networks for Time Series Prediction through Harmony Search". International Journal of Machine Learning and Computing 11, n.º 4 (agosto de 2021): 274–80. http://dx.doi.org/10.18178/ijmlc.2021.11.4.1047.
Texto completo da fonteYe, Zilin. "Application of Improved Deep Belief Network Model in 3D Art Design". Mathematical Problems in Engineering 2022 (5 de abril de 2022): 1–9. http://dx.doi.org/10.1155/2022/2213561.
Texto completo da fonteWei, Yuan, Huanchang Zhang, Jiahui Dai, Ruili Zhu, Lihong Qiu, Yuzhuo Dong e Shuai Fang. "Deep Belief Network with Swarm Spider Optimization Method for Renewable Energy Power Forecasting". Processes 11, n.º 4 (26 de março de 2023): 1001. http://dx.doi.org/10.3390/pr11041001.
Texto completo da fontePatil, Balasaheb H. "Effect of Optimized Deep Belief Network to Patch-Based Image Inpainting Forensics". International Journal of Swarm Intelligence Research 13, n.º 3 (1 de julho de 2022): 1–21. http://dx.doi.org/10.4018/ijsir.304401.
Texto completo da fonteLi, Zhengying, Hong Huang, Zhen Zhang e Guangyao Shi. "Manifold-Based Multi-Deep Belief Network for Feature Extraction of Hyperspectral Image". Remote Sensing 14, n.º 6 (19 de março de 2022): 1484. http://dx.doi.org/10.3390/rs14061484.
Texto completo da fonteWang, Xiangqian, Fang Huang, Wencong Wan e Chengyuan Zhang. "Academic Activities Transaction Extraction Based on Deep Belief Network". Advances in Multimedia 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/5067069.
Texto completo da fonteCai, Yulin, Puran Fan, Sen Lang, Mengyao Li, Yasir Muhammad e Aixia Liu. "Downscaling of SMAP Soil Moisture Data by Using a Deep Belief Network". Remote Sensing 14, n.º 22 (10 de novembro de 2022): 5681. http://dx.doi.org/10.3390/rs14225681.
Texto completo da fonteZeng, Qingwen, Chunyan Hu, Jiaxian Sun, Yafeng Shen e Keqiang Miao. "Monitoring of Thermoacoustic Combustion Instability via Recurrence Quantification Analysis and Optimized Deep Belief Network". Symmetry 16, n.º 3 (22 de fevereiro de 2024): 266. http://dx.doi.org/10.3390/sym16030266.
Texto completo da fonteYu, He, Zaike Tian, Hongru Li, Baohua Xu e Guoqing An. "A Novel Deep Belief Network Model Constructed by Improved Conditional RBMs and its Application in RUL Prediction for Hydraulic Pumps". International Journal of Acoustics and Vibration 25, n.º 3 (30 de setembro de 2020): 373–82. http://dx.doi.org/10.20855/ijav.2020.25.31669.
Texto completo da fonteWang, Ching-Hsin, Kuo-Ping Lin, Yu-Ming Lu e Chih-Feng Wu. "Deep Belief Network with Seasonal Decomposition for Solar Power Output Forecasting". International Journal of Reliability, Quality and Safety Engineering 26, n.º 06 (dezembro de 2019): 1950029. http://dx.doi.org/10.1142/s0218539319500293.
Texto completo da fonteObaid, Ahmed J., e Hassanain K. Alrammahi. "An Intelligent Facial Expression Recognition System Using a Hybrid Deep Convolutional Neural Network for Multimedia Applications". Applied Sciences 13, n.º 21 (5 de novembro de 2023): 12049. http://dx.doi.org/10.3390/app132112049.
Texto completo da fonteTian, Shengwei, Yilin Yan, Long Yu, Mei Wang e Li Li. "Prediction of Anti-Malarial Activity Based on Deep Belief Network". International Journal of Computational Intelligence and Applications 17, n.º 03 (setembro de 2018): 1850012. http://dx.doi.org/10.1142/s1469026818500128.
Texto completo da fonteZhu, Chang-Hao, e Jie Zhang. "Developing Soft Sensors for Polymer Melt Index in an Industrial Polymerization Process Using Deep Belief Networks". International Journal of Automation and Computing 17, n.º 1 (5 de novembro de 2019): 44–54. http://dx.doi.org/10.1007/s11633-019-1203-x.
Texto completo da fonteYu, Long, Xinyu Shi, Shengwei Tian, Shuangyin Gao e Li Li. "Classification of Cytochrome P450 1A2 Inhibitors and Noninhibitors Based on Deep Belief Network". International Journal of Computational Intelligence and Applications 16, n.º 01 (março de 2017): 1750002. http://dx.doi.org/10.1142/s146902681750002x.
Texto completo da fonte