搜索extreme learning machine共有 13 个结果
1
Prediction of concrete compressive strength based on tuna swarm algorithm optimization extreme learning machine
2024年第2期 : 444-449
doi:10.19734/j.issn.1001-3695.2023.05.0237
2
Robust extreme learning machine based on p order maximum correntropy criterion loss function
2021年第12期 : 3683-3687
doi:10.19734/j.issn.1001-3695.2021.03.0136
3
Research and parallel optimization of Parkinson's disease early diagnosis model based on improved salp swarm algorithm
2021年第9期 : 2726-2731
doi:10.19734/j.issn.1001-3695.2020.11.0547
4
Adaptive and momentum method for regularized extreme learning machine
2021年第6期 : 1724-1727,1764
doi:10.19734/j.issn.1001-3695.2020.08.0186
5
Soft sensor modeling of extreme learning machine based on improved particle swarm optimization
2020年第6期 : 1683-1687
doi:10.19734/j.issn.1001-3695.2018.11.0863
6
Real-time classification algorithm of remote sensing images based on ant colony optimization algorithm and independent feature sets
2020年第2期 : 573-577
doi:10.19734/j.issn.1001-3695.2018.06.0574
7
New algorithm for input weight of single hidden layer neural network
2019年第12期 : 3666-3669
doi:10.19734/j.issn.1001-3695.2018.07.0418
8
Gene expression data classification method based on FCBF feature selection and ensemble optimized learning
2019年第10期 : 2986-2991
doi:10.19734/j.issn.1001-3695.2018.04.0248
9
Research on methods of robot accuracy compensation based on PSO-ELM
2019年第10期 : 3000-3003
doi:10.19734/j.issn.1001-3695.2018.03.0210
10
Parallel network intrusion detection method based on ReliefF and improved crow search optimization
2019年第10期 : 3063-3068
doi:10.19734/j.issn.1001-3695.2018.06.0309
11
Semi-supervised auto-encoder using sparse and label regularizations for classification
2019年第9期 : 2613-2617
doi:10.19734/j.issn.1001-3695.2018.02.0147
12
Improved method of optimal fish swarm optimization for industrial control network communication anomaly detection
2019年第7期 : 2164-2168,2178
doi:10.19734/j.issn.1001-3695.2018.01.0099
13
Hybrid CNN-ELM model for short text classification
2019年第3期 : 663-667,672
doi:10.19734/j.issn.1001-3695.2017.09.0930