Mercury Contamination in Environment Surrounding Coal-Fired Power Plant

Chinwetkitvanich, Sopa

doi:10.21660/2017.33.2581

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…As a lethal and hugely volatile metal, mercury can cause contamination of surface streams and lakes, as well as groundwater [21]. It is the most dangerous hazard for infants and young adults as it influences the central nervous system, causing severe illnesses [22]. Previous studies (e.g., [7][8][9][10][11]) report that a substantial amount of mercury outflows into the environment come from coal-fired power plants.…”

Section: Introductionmentioning

confidence: 99%

Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

et al. 2019

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Accurate prediction of mercury content emitted from fossil-fueled power stations is of the utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations’ boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model included coal characteristics and the operational parameters of the boilers. The dataset was collected from 82 sample points in power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of the ANFIS-PSO, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively. Furthermore, relative errors between the acquired data and predicted values were between −0.25% and 0.1%, which confirm the accuracy of the model to deal non-linearity and represent the dependency of flue gas mercury content into the specifications of coal and the boiler type.

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Section: Introductionmentioning

confidence: 99%

Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

et al. 2019

View full text Add to dashboard Cite

show abstract

Developing ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

Shamshirband¹,

Hadipoor²,

Baghban³

et al. 2019

Preprint

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Accurate prediction of mercury content emitted from fossil-fueled power stations is of utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations' boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model include coal characteristics and the operational parameters of the boilers. The dataset has been collected from 82 power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of ANFIS-PSO model, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively.Furthermore, relative errors between acquired data and predicted values were between -0.25% and 0.1%, which confirm the accuracy of the model to deal nonlinearity and representing the dependency of flue gas mercury content into the specifications of coal and the boiler type.

show abstract

Mercury Contamination in Environment Surrounding Coal-Fired Power Plant

Cited by 2 publications

References 14 publications

Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

Developing an ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

Developing ANFIS-PSO Model to Predict Mercury Emissions in Combustion Flue Gases

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