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Author:

王龙洋 (王龙洋.) | 蒙西 (蒙西.) | 乔俊飞 (乔俊飞.) (Scholars:乔俊飞)

Indexed by:

EI Scopus CSCD

Abstract:

出水总磷的准确预测对于城市污水处理厂的高效、稳定的运行至关重要。文中针对城市污水处理过程中出水总磷难以预测的问题,提出一种基于改进集合经验模态分解(modified ensemble empirical mode decomposition, MEEMD)和深度信念网络(deep belief network, DBN)的出水总磷预测方法。首先,设计一种MEEMD算法对城市污水处理过程出水总磷数据信号进行分解,获取多个本征模态函数(intrinsic mode function,IMF)组合;然后,建立一种基于模拟退火(simulated annealing, SA)算法的深度信念网络预测模型...

Keyword:

集合经验模态分解 城市污水处理过程 深度信念网络 出水总磷

Author Community:

  • [ 1 ] 北京工业大学信息学部
  • [ 2 ] 计算智能与智能系统北京市重点实验室

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Source :

化工学报

Year: 2021

Issue: 05

Volume: 72

Page: 2745-2753

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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