Inicio  /  Water  /  Vol: 10 Núm: 1 Par: January (2018)  /  Artículo
ARTÍCULO
TITULO

Using a Backpropagation Artificial Neural Network to Predict Nutrient Removal in Tidal Flow Constructed Wetlands

Wei Li    
Lijuan Cui    
Yaqiong Zhang    
Zhangjie Cai    
Manyin Zhang    
Weigang Xu    
Xinsheng Zhao    
Yinru Lei    
Xu Pan    
Jing Li and Zhiguo Dou    

Resumen

No disponible

 Artículos similares

       
 
Yongtao Lyu, Yibiao Niu, Tao He, Limin Shu, Michael Zhuravkov and Shutao Zhou    
In this paper, a new method using the backpropagation (BP) neural network combined with the improved genetic algorithm (GA) is proposed for the inverse design of thin-walled reinforced structures. The BP neural network model is used to establish the mapp... ver más
Revista: Aerospace

 
Shuo Wang, Kailun Feng and Yaowu Wang    
In construction planning, decision making has a great impact on final project performance. Hence, it is essential for project managers to assess the construction planning and make informed decisions. However, disproportionately large uncertainties occur ... ver más
Revista: Buildings

 
Ningning Liu, Danfeng Xie, Changlong Wang and Yun Bai    
Scholars have paid considerable attention to the factors that affect the safety states of construction workers. However, only a few studies have focused on the safety assessment and security alerts of individual workers. In this study, the term ?frequenc... ver más
Revista: Applied Sciences

 
Mingyu Zhang, Fei Gao, Wuping Yang and Haoran Zhang    
In this paper, we propose a wildlife detection algorithm based on improved YOLOv5s by combining six real wildlife images of different sizes and forms as datasets. Firstly, we use the RepVGG model to simplify the network structure that integrates the idea... ver más
Revista: Applied Sciences

 
Rong Zhou, Zhisheng Zhang and Yuan Wang    
Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas; however, the low training efficiency and high demand for samples are problems that limit the application. Ins... ver más
Revista: Applied Sciences