Cargando…
Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion
For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and b...
Autores principales: | Wang, Jie-sheng, Han, Shuang, Shen, Na-na |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005072/ https://www.ncbi.nlm.nih.gov/pubmed/24982935 http://dx.doi.org/10.1155/2014/262368 |
Ejemplares similares
-
Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm
por: Wang, Jie-sheng, et al.
Publicado: (2014) -
Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm
por: Wang, Jie-Sheng, et al.
Publicado: (2015) -
The Application of Internet of Things in Robot Route Planning Based on Multisource Information Fusion
por: Yao, Yunfeng, et al.
Publicado: (2022) -
Work and the ESN School-Leaver
por: Hoxter, Hans
Publicado: (1969) -
Intelligent Assessment of Mental Health Based on Multisource Information Fusion
por: Jing, Yumei
Publicado: (2022)