Adaptive Neuro-Fuzzy Inference system analysis on adsorption studies of Reactive Red 198 from aqueous solution by SBA-15/CTAB composite

In the present review, we have been able to describe the different families of dyes and pigments used in textile finishing processes (Yarns, fabrics, nonwovens, knits and rugs) such as dyeing and printing. These dyes are reactive, direct, dispersed, indigo, sulphur and vats. Such that their presence in the liquid effluents resulting from the textile washing constitutes a serious risk, in the absence of their purification, for the quality of receiving aquatic environments. Indeed, the presence of these dyes and pigments can cause a significant alteration in the ecological conditions of the aquatic fauna and flora, because of the lack of their biodegradability. This has a negative impact on the equilibrium of the aquatic environment by causing serious dangers, namely the obvious dangers (Eutrophication, under-oxygenation, color, turbidity and odor), the long-term dangers (Persistence, bioaccumulation of carcinogenic aromatic products and formation of by-products of chlorination), mutagenicity and carcinogenicity.

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“…On the other hand, their main disadvantage is their low wet strength. Table 13 below gives some examples of direct dyes [58, 59].…”

Section: Main Textmentioning

confidence: 99%

Textile finishing dyes and their impact on aquatic environs

Berradi

Hsissou

Khudhair

et al. 2019

Heliyon

577

208

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“…ANFIS consists of five layers, namely, a fuzzy layer, a product layer, a normalized layer, a defuzzy layer and a total output layer [27,37]. In the first and fourth layers, the nodes are adaptive and some used parameters in these nodes are determined through training phase, whereas the nodes in other layers are fixed.…”

Section: Anfis Theorymentioning

confidence: 99%

Neuro-fuzzy modeling to adsorptive performance of magnetic chitosan nanocomposite

2016

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In the present paper, the adaptive neural fuzzy inference system (ANFIS) was used for modeling of magnetic chitosan adsorption performance for the methyl orange removal. The ANFIS network, which is the best in data predicting, was trained with back propagation optimum method. Our results revealed that the developed ANFIS models can effectively model the non-linearity behavior of the adsorptive performance and the predicted values were in good agreement with the experimental data.

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“…The Gaussian membership function is reported in the literature as a useful tool to obtain the predicted values with higher accuracy [19,21,32] and, therefore, was adopted to describe the memberships of the heating rate and the temperature. The memberships of the heating rate and the temperature are expressed as following equations,…”

Section: Adaptive Neural Fuzzy Modelmentioning

confidence: 99%

Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis

Pan

Duque

Martins

et al. 2020

Heliyon

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In the present study, the waste polyethylene (PE) pyrolysis under different non-isothermal conditions was investigated to estimate the optimal conversions and pyrolysis rates. The pyrolysis study was carried out using Thermogravimetry (TG) of the virgin and the waste PE under different heating rates of 5, 10, 15 and 20 C/min. The TG experiments indicated that the virgin and the waste PE pyrolysis processes mainly underwent in the temperature range of 390-510 C. Subsequently, the adaptive neural fuzzy model was adopted to predict the conversions and the pyrolysis rates of the virgin and the waste PE. The optimal operating conditions in different temperature ranges were optimized by the simulated annealing algorithm (SA). Moreover, the R-squared values of the virgin PE conversions (~1) and pyrolysis rates (> 0.999), and the waste PE conversions (~1) and pyrolysis rates (> 0.999) revealed the high accuracy of the adaptive neural fuzzy model predicted results.

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Adaptive Neuro-Fuzzy Inference system analysis on adsorption studies of Reactive Red 198 from aqueous solution by SBA-15/CTAB composite

Cited by 23 publications

References 33 publications

Textile finishing dyes and their impact on aquatic environs

Textile finishing dyes and their impact on aquatic environs

Neuro-fuzzy modeling to adsorptive performance of magnetic chitosan nanocomposite

Application of a neural fuzzy model combined with simulated annealing algorithm to predict optimal conditions for polyethylene waste non-isothermal pyrolysis

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