Results 261 to 270 of about 901,615 (325)

Gaussian Mixture Model Clustering with Incomplete Data

ACM Trans. Multim. Comput. Commun. Appl., 2021
Gaussian mixture model (GMM) clustering has been extensively studied due to its effectiveness and efficiency. Though demonstrating promising performance in various applications, it cannot effectively address the absent features among data, which is not ...
Yi Zhang, Miaomiao Li, Siwei Wang, Sisi Dai, Lei Luo, En Zhu, Huiying Xu, Xinzhong Zhu, Chaoyun Yao, Hao Zhou   +9 more
semanticscholar   +1 more source

An effective convolutional neural network based on SMOTE and Gaussian mixture model for intrusion detection in imbalanced dataset

Comput. Networks, 2020
Network Intrusion Detection System (NIDS) is a key security device in modern networks to detect malicious activities. However, the problem of imbalanced class associated with intrusion detection dataset limits the classifier’s performance for minority ...
Hongpo Zhang, Lulu Huang, C. Wu, Zhanbo Li   +3 more
semanticscholar   +1 more source

Fuzzy Gaussian Mixture Models

Pattern Recognition, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ju, Zhaojie, Liu, Honghai
openaire   +2 more sources

Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model

, 2020
The establishment of an accurate and reliable forecasting model is important for water resource planning and management. In this study, we developed a hybrid model (namely GMM-XGBoost), coupling extreme gradient boosting (XGBoost) with Gaussian mixture ...
Lingling Ni, Dong Wang, Jianfeng Wu, Yuankun Wang, Yuwei Tao, Jianyun Zhang, Jiu-fu Liu   +6 more
semanticscholar   +1 more source

Analytical Reformulation for Stochastic Unit Commitment Considering Wind Power Uncertainty With Gaussian Mixture Model

IEEE Transactions on Power Systems, 2020
To capture the stochastic characteristics of renewable energy generation output, chance-constrained unit commitment (CCUC) model is widely used. Conventionally, analytical reformulation for CCUC is usually based on simplified probability assumption or ...
Yuelin Yang, Wenchuan Wu, Bin Wang, Mingjie Li   +3 more
semanticscholar   +1 more source

Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques

Cognitive Systems Research, 2019
Objectives Liver cancer is one of the leading cause of death in all over the world. Detecting the cancer tissue manually is a difficult task and time consuming.
Amita Das, U. R. Acharya, U. R. Acharya, U. R. Acharya, S. S. Panda, S. Sabut   +5 more
semanticscholar   +1 more source

Gaussian mixture model with feature selection: An embedded approach

Computers & industrial engineering, 2020
Gaussian Mixture Model (GMM) is a popular clustering algorithm due to its neat statistical properties, which enable the “soft” clustering and the determination of the number of clusters.
Yinlin Fu, Xiaonan Liu, Suryadipto Sarkar, Teresa Wu   +3 more
semanticscholar   +1 more source

Fault diagnosis of VRF air-conditioning system based on improved Gaussian mixture model with PCA approach

, 2020
The timely fault diagnosis of HVAC systems is important for building energy saving, equipment maintenance and indoor comfort. The Gaussian mixture model method has rarely been studied in the fault diagnosis application of HVAC systems. Therefore, a novel
Yabin Guo, Huanxin Chen
semanticscholar   +1 more source

Guide to Match: Multi-Layer Feature Matching With a Hybrid Gaussian Mixture Model

IEEE transactions on multimedia, 2020
As a fundamental yet challenging task in computer vision, finding correspondences between two sets of feature points has received extensive attention.
Kun Sun, Wenbing Tao, Y. Qian
semanticscholar   +1 more source

Real-time anomaly detection based on long short-Term memory and Gaussian Mixture Model

Computers & electrical engineering, 2019
Anomaly detection is a long-standing problem in system designation. High-quality anomaly detection can benefit plenty of applications (e.g. system monitoring, disaster precaution and intrusion detection).
N. Ding, Haoxuan Ma, Huanbo Gao, Yanhua Ma, Guozhen Tan   +4 more
semanticscholar   +1 more source