Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks

Chen, Yifeng; Shen, Liguo; Li, Renjie; Xu, Xianchao; Hong, Huachang; Lin, Hongjun; Chen, Jianrong

doi:10.1016/j.jcis.2020.01.003

Cited by 95 publications

(28 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Extended DVLO (XDLVO) model [49] builds on the DLVO theory by taking hydrophobic interactions into consideration. The XDLVO theory can predict interactions of dissolved and colloidal materials with various surfaces [50] , [51] and has been applied to describe virus-surface interactions [21] , [25] , [33] , [52] . The XDLVO theory describes the total energy of interaction

between two surfaces in an aqueous medium as a sum of the Lifshitz-van der Waals,

, electrostatic double layer,

, an acid-base,

, energies.…”

Section: Methodsmentioning

confidence: 99%

Lip balm drying promotes virus attachment: Characterization of lip balm coatings and XDLVO modeling

Wang

Şengür-Taşdemir

Koyuncu

et al. 2021

Journal of Colloid and Interface Science

View full text Add to dashboard Cite

show abstract

between two surfaces in an aqueous medium as a sum of the Lifshitz-van der Waals,

, electrostatic double layer,

, an acid-base,

, energies.…”

Section: Methodsmentioning

confidence: 99%

Lip balm drying promotes virus attachment: Characterization of lip balm coatings and XDLVO modeling

Wang

Şengür-Taşdemir

Koyuncu

et al. 2021

Journal of Colloid and Interface Science

View full text Add to dashboard Cite

show abstract

“…The GRNN contains input, hidden, summation, and output layers. 54 In this research, the controller has two inputs and one output. The power generated error of DGs is considered an economic error in this investigation.…”

Section: Grnn For Load Frequency Deviation Analysismentioning

confidence: 99%

Hybrid technique for load frequency control of renewable energy sources with unified power flow controller and energy storage integration

Munisamy

Sundarajan

2021

Intl J of Energy Research

View full text Add to dashboard Cite

In this manuscript, the load frequency control (LFC) of multiple area hybrid power system (PS) integrated with renewable energy sources (RESs) using energy storage system (ESS) is proposed. The proposed hybrid method is the joint execution of Meta-heuristic Anopheles Search Algorithm (MASA) and artificial intelligence (AI) technique and hence it is named as MASAAI technique. The main aim of the proposal is "to diminish the load frequency deviations in 3-area hybrid PS." The thyristor controlled phase shifter (TCPS) and ultra-capacitor (UC) application are used in LFC. During the operation of power system, the power distribution quality is suffered owing to continual and random changes in load. Hence, the PS control is necessary for maintaining a continual balance amid the power generation and load demand. The proportional integral derivative (PID) is agreed to LFC mode. Here, the 3-area system is incorporated with conventional RESs like solar, biomass, and fuel cell. UPFC is joined in series with tie-line, ensures the stabilization of the system and also presents more service and the quality of power is sustained by the subordinate control of super capacitor energy storage. With the help of MASAAI method, suppressing the peak value of the frequency deviation by power modulation control is a way to lessen this issue. With this proper control, the MASAAI method efficiency becomes optimum in deregulated environment that is agreed to LFC mode. Finally, the proposed method is activated in MATLAB/Simulink site and the performance is compared with existing methods. Finally, the simulation outcomes demonstrate that the efficiency of MASAAI method is more efficient compared to the existing methods. K E Y W O R D S artificial intelligence (AI) technique, frequency deviation, load frequency control, metaheuristic anopheles search algorithm (MASA)

show abstract

“…The neural network model for evaluation of water circulation health in Hebei takes each influencing index in each set of data as input and the regional water circulation health index as the output, so there are 16 neurons in the input layer and 1 in the target layer. For a more complex BP neural network, the number of hidden layers also needs to be determined through calculation [24]. The number of neurons in the hidden layer is determined by formula (1):…”

Section: Determination Of the Network Structure Of The Evaluation Modelmentioning

confidence: 99%

Regional Water Circulation Health Evaluation System Based on Artificial Neural Network

Lv¹,

Zhang²,

Wang³

et al. 2020

IJDNE

View full text Add to dashboard Cite

Whether the urban water circulation is healthy or not is an issue that must be considered for achieving the sustainable development of urban society. Before promoting the urban water circulation health system for Hebei Province, it is necessary to evaluate the status of water circulation in this Province. First of all, this paper establishes a regional water circulation health evaluation index system for Hebei Province, and then it builds a regional water circulation health evaluation model for Hebei based on BP artificial neural network. Finally, the evaluation results of water circulation health in Hebei province during the period of 2004-2017 are obtained. This evaluation model can provide background support for the ecological civilization construction and sustainable development of Hebei Province, and serve as a strategic basis for solving urban water problems.

show abstract

Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks

Cited by 95 publications

References 41 publications

Lip balm drying promotes virus attachment: Characterization of lip balm coatings and XDLVO modeling

Lip balm drying promotes virus attachment: Characterization of lip balm coatings and XDLVO modeling

Hybrid technique for load frequency control of renewable energy sources with unified power flow controller and energy storage integration

Regional Water Circulation Health Evaluation System Based on Artificial Neural Network

Contact Info

Product

Resources

About