Analysis of aerobic granular sludge formation based on grey system theory

Zhang, Cuiya; Zhang, Hanmin

doi:10.1016/s1001-0742(12)60080-1

Cited by 11 publications

(4 citation statements)

References 32 publications

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“…Because of the noise from both inside and outside of the system, the information we can reach about that system is always uncertain and limited in scope. [ 21 , 27 ]…”

Section: Discussionmentioning

confidence: 99%

The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China

et al. 2018

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Typhoid and paratyphoid fevers (TPF), systemic emerging infectious diseases, is a serious health problem for society. If the incidence trend of TPF can be predicted, prevention and control measures can be taken in advance to reduce the harm to the people's health.Grey Model First Order One Variable [GM (1, 1)] was applied to predict the incidence trend of TPF with the incidence data of TPF in Wuhan City of China from 2004 to 2015. The original data were acquired from the national surveillance system.The GM (1, 1) model was established as ŷ (t + 1) = 0.88 e−0.21t + 0.15. The goodness-of-fit test indicated that the precision (degree 2) was qualified (C = 0.40, P = .91). We further compared actual values with predicted values in 2016 and found that GM (1, 1) model we built has excellent performance in incidence trend prediction.Our prediction shows that the TPF incidences in Wuhan City will be slowly decreasing in the next 3 years. It is, however, still necessary to strengthen the comprehensive prevention and control to reduce the incidence level of TPF.

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“…Because of the noise from both inside and outside of the system, the information we can reach about that system is always uncertain and limited in scope. [ 21 , 27 ]…”

Section: Discussionmentioning

confidence: 99%

The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China

et al. 2018

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“…The gray theory was proposed by Deng (Deng, 1982; Deng, 1989), which included gray relational analysis (GRA). GRA is an effective method to analyze uncertain correlations between things and system factors, or factors and the main behavior, and enable investigation of quantitative and qualitative relationships using relatively little data or with considerable variability in factors (Deng 1982; Deng, 1989; Wang et al, 2009; Liu and Lin, 2010; Zhang and Zhang, 2013; Guo and Kang, 2018). In addition, because there is no restriction on the type of samples and the probability distribution, GRA has been widely applied in diverse fields of research (Wang et al, 2009; Zhang and Zhang, 2013; Guo and Kang, 2018; Sun et al, 2018; Wang et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

Illumination/Darkness-Induced Changes in Leaf Surface Potential Linked With Kinetics of Ion Fluxes

Yang

Wang

et al. 2019

Front. Plant Sci.

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A highly reproducible plant electrical signal–light-induced bioelectrogenesis (LIB) was obtained by means of periodic illumination/darkness stimulation of broad bean (Vicia faba L.) leaves. By stimulating the same position of the same leaf with different concentrations of NaCl, we observed that the amplitude and waveform of the LIB was correlated with the intensity of stimulation. This method allowed us to link dynamic ion fluxes induced by periodic illumination/darkness to salt stress. The self-referencing ion electrode technique was used to explore the ionic mechanisms of the LIB. Fluxes of H+, Ca2+, K+, and Cl− showed periodic changes under periodic illumination/darkness before and after 50 mM NaCl stimulation. Gray relational analysis was used to analyze correlations between each of these ions and LIB. The results showed that different ions are involved in surface potential changes at different stages under periodic illumination/darkness. The gray relational grade reflected the contribution of each ion to the change in surface potential at a certain time period. The ion fluxes data obtained under periodic illumination/darkness stimulation will contribute to the future development of a dynamic model for interpretation of electrophysiological events in plant cells.

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“…However, the method requires a reliable model that can characterize causal associations. Due to the complexity, uncertainty, and high nonlinearity of biochemical reactions in wastewater treatment, models designed using grey model methods [13], parametric evaluation methods [14], and statistical analysis methods [15] are difficult to characterize.…”

Section: Related Workmentioning

confidence: 99%

Research on Wastewater Treatment Monitoring Algorithms Based on Deep Convolutional Neural Networks

Zhang

2022

Wireless Communications and Mobile Computing

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Around the problems of data loss, noise, and different temporal and spatial scale features of urban wastewater treatment process data, a method of monitoring and predicting wastewater treatment process data based on deep convolutional neural networks is proposed in the paper. Firstly, to address the problem that urban wastewater treatment process data has multiple spatial and temporal scale characteristics, which makes it difficult for the data to be used effectively, a spatial and temporal data fusion model based on fuzzy neural network (FNN) is proposed. Fuzzy neural networks have strong generalization ability and robustness. Secondly, to enable accurate and real-time monitoring of the content of the monitored components in the effluent of the urban wastewater treatment process, an intelligent prediction model based on SDF-FNN is established for the effluent. Finally, in order to verify the effectiveness of this intelligent prediction model, the model is tested using data collected from actual municipal wastewater treatment plants. The experimental results show that the wastewater treatment intelligent monitoring model is effective and can predict the content of the effluent monitoring index with high accuracy.

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Analysis of aerobic granular sludge formation based on grey system theory

Cited by 11 publications

References 32 publications

The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China

The analysis of GM (1, 1) grey model to predict the incidence trend of typhoid and paratyphoid fevers in Wuhan City, China

Illumination/Darkness-Induced Changes in Leaf Surface Potential Linked With Kinetics of Ion Fluxes

Research on Wastewater Treatment Monitoring Algorithms Based on Deep Convolutional Neural Networks

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