Výsledky vyhledávání - "improved conditional variational autoencoder"

A Radio Map Estimation Method Based on Improved Conditional Variational Autoencoder

Autoři: Zhuang An Zheng Dou Qi Liu a další

Zdroj: 2024 International Conference on Intelligent Communication, Sensing and Electromagnetics (ICSE). :9-13

Daily Power Scenario Generation Method for Multiple Wind Farms Based on Gaussian Mixture Clustering and Improved Conditional Variational Autoencoder

Autoři: Dan LI Yunyan LIANG Shuwei MIAO a další

Zdroj: Zhongguo dianli, Vol 57, Iss 12, Pp 17-29 (2024)

Témata: QC501-721, hyperspherical distribution, TK1001-1841, Production of electric energy or power. Powerplants. Central stations, Electricity, feature extraction, wind power scenario generation, conditional variational autoencoder, gaussian mixture model, regularization technique

Přístupová URL adresa: https://doaj.org/article/4465b91aecc5458fbe897fd9f023c8fb

A Hybrid Model for QoS Prediction based on Improved Conditional Variational Autoencoder

Autoři: Mengwei Wu Qin Lu Yingxue Wang a další

Zdroj: 2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). :339-346

The Recommendation Algorithm Based on Improved Conditional Variational Autoencoder and Constrained Probabilistic Matrix Factorization

Autoři: Yunfei Zhang Hongzhen Xu Xiaojun Yu

Zdroj: Applied Sciences, Vol 13, Iss 21, p 12027 (2023)

Témata: collaborative filtering, conditional variational autoencoder, constrained probabilistic matrix factorization, auxiliary information, feature matric, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2076-3417/13/21/12027; https://doaj.org/toc/2076-3417

Přístupová URL adresa: https://doaj.org/article/626d905e644d47f09bec7f9431b82667

Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network

Autoři: Yanqing Yang Kangfeng Zheng Chunhua Wu a další

Zdroj: Sensors, Vol 19, Iss 11, p 2528 (2019)

Témata: intrusion detection, variational inference, improved conditional variational autoencoder, generator network, deep neural network, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/19/11/2528; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/992c6ab3bdf848209c95c98257738587

基于高斯混合聚类和改进条件变分自编码的 多风电场功率日场景生成方法. (Chinese)

Alternate Title: Daily Power Scenario Generation Method for Multiple Wind Farms Based on Gaussian Mixture Clustering and Improved Conditional Variational Autoencoder. (English)

Autoři: 李丹 梁云嫣 缪书唯 a další

Zdroj: Electric Power; Dec2024, Vol. 57 Issue 12, p17-29, 13p

The Recommendation Algorithm Based on Improved Conditional Variational Autoencoder and Constrained Probabilistic Matrix Factorization.

Autoři: Zhang, Yunfei Xu, Hongzhen Yu, Xiaojun

Zdroj: Applied Sciences (2076-3417); Nov2023, Vol. 13 Issue 21, p12027, 18p

Témata: RECOMMENDER systems, MATRIX decomposition, FACTORIZATION, STANDARD deviations, MATRIX multiplications, FEATURE extraction, ALGORITHMS

Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network.

Autoři: Yang, Yanqing Zheng, Kangfeng Wu, Chunhua a další

Zdroj: Sensors (14248220); Jun2019, Vol. 19 Issue 11, p2528, 1p

Témata: ARTIFICIAL neural networks, GLOBAL optimization, MACHINE learning

GWO-LightGBM: A Hybrid Grey Wolf Optimized Light Gradient Boosting Model for Cyber-Physical System Security.

Autoři: Munawar, Adeel Ali, Muhammad Nadeem Qasim, Awais a další

Zdroj: Computer Modeling in Engineering & Sciences (CMES); 2025, Vol. 145 Issue 1, p1189-1211, 23p

Témata: CYBER physical systems, INTRUSION detection systems (Computer security), GREY Wolf Optimizer algorithm, BOOSTING algorithms, MACHINE learning, FEATURE selection, INTERNET security, REAL-time computing

Enhancing intrusion detection: protocol-based security using a hybrid RIDGE classifier on InSDN, UNSW-NB15, BoT-IoT, and ToN-IoT datasets.

Autoři: Nemalikanti, Anand Kaki, Sreenija Ambati, Rami Reddy a další

Zdroj: Cluster Computing; Oct2025, Vol. 28 Issue 10, p1-26, 26p

Témata: INTRUSION detection systems (Computer security), INTERNET of things, DATA transformations (Statistics), DEEP learning, SOFTWARE-defined networking, DATA libraries, EVALUATION methodology

Self-learning model fusion for network anomaly detection: A hybrid CNN-LSTM-transformer framework.

Autoři: Wang, Jun Huang, Ning Zhang, Houzhong a další

Zdroj: PLoS ONE; 10/29/2025, Vol. 20 Issue 10, p1-21, 21p

Témata: ANOMALY detection (Computer security), CONVOLUTIONAL neural networks, INTERNET security, AUTOMATICITY (Learning process), MACHINE learning, ENSEMBLE learning, TRANSFORMER models, LONG short-term memory

Agm-c3banet: a network intrusion detection model for imbalanced data.

Autoři: Chen, Xin Zhang, Yuejin Gong, Zhongyuan a další

Zdroj: Cluster Computing; 2025, Vol. 28 Issue 8, p1-19, 19p

An improved sensor fault in-situ calibration strategy for building HVAC systems with forgetting-adaptive mechanism based on data incremental learning.

Autoři: Li, Guannan Kuang, Wei Li, Wei a další

Zdroj: Building Simulation; Sep2025, Vol. 18 Issue 9, p2345-2364, 20p

考虑新能源不确定性的电力系统灵活性评价方法与提升措施. (Chinese)

Alternate Title: Power System Flexibility Evaluation Method and Improvement Measures Considering New Energy Uncertainty. (English)

Autoři: 冯树海 史新红 郑亚先 a další

Zdroj: Shandong Electric Power; 2025, Vol. 52 Issue 9, p32-43, 12p

Témata: ELECTRIC power systems, RENEWABLE energy sources, SCHEDULING, MATHEMATICAL optimization, UNCERTAINTY (Information theory)

An Enhanced Intrusion Detection System Using Attention-Based Stacked Sparse Autoencoder Feature Extraction.

Autoři: Varanasi, Venkata Ramani Razia, Shaik

Zdroj: Engineering, Technology & Applied Science Research; Aug2025, Vol. 15 Issue 4, p24436-24441, 6p

Témata: INTRUSION detection systems (Computer security), FEATURE extraction, SIGNAL denoising, LONG short-term memory, ARTIFICIAL neural networks, BIG data, MACHINE learning

基于注意力机制和 RCN-BiLSTM 融合的 风电机组故障识别. (Chinese)

Alternate Title: Fault Identification for Wind Turbine Based on Attention Mechanism and RCN-BiLSTM Fusion. (English)

Autoři: 陈小乾 尹亮 展宗辉 a další

Zdroj: Electric Power; Aug2025, Vol. 58 Issue 8, p94-102, 9p

Témata: LONG short-term memory, CAPSULE neural networks, WIND turbines, SUPERVISORY control systems, ACQUISITION of data

Online Network DoS/DDoS Detection: Sampling, Change Point Detection, and Machine Learning Methods.

Autoři: Owusu, Evans Rahouti, Mohamed Kumar Jagatheesaperumal, Senthil a další

Zdroj: IEEE Communications Surveys & Tutorials; Aug2025, Vol. 27 Issue 4, p2543-2580, 38p

TopoSMOTE: 基于拓扑数据分析的网络 入侵检测不平衡学习. (Chinese)

Alternate Title: network intrusion detection; topological data analysis; imbalanced learning; data augmentation. (English)

Autoři: 闫计栋 钟美荟 周帆

Zdroj: Science Technology & Engineering; 2025, Vol. 25 Issue 19, p8142-8150, 9p

Témata: COMPUTER network traffic, DATA analysis, DATA augmentation, INTRUSION detection systems (Computer security), INTERNET security, FALSE alarms, MINORITIES

Intelligent Detection of Abnormal Traffic Based on SCN-BiLSTM.

Autoři: Zhang, Lulu Du, Xuehui Wang, Wenjuan a další

Zdroj: Computers, Materials & Continua; 2025, Vol. 84 Issue 1, p1901-1919, 19p

Témata: CONVOLUTIONAL neural networks, LONG short-term memory, TRAFFIC monitoring, FEATURE extraction, GENERALIZATION

Challenges in detecting security threats in WoT: a systematic literature review.

Autoři: Sardar, Ruhma Anees, Tayyaba Al-Shamayleh, Ahmad Sami a další

Zdroj: Artificial Intelligence Review; Jul2025, Vol. 58 Issue 7, p1-57, 57p

Témata: DENIAL of service attacks, ARTIFICIAL intelligence, DEEP learning, CONVOLUTIONAL neural networks, SECURITY systems