Application of adaptive neuro-fuzzy interference system on biosorption of malachite green using fir (<i>Abies nordmanniana)</i> cones biomass

Sacara, Ana Maria; Indolean, Cerasella; Cristea, Mircea Vasile; Mureşan, Liana Maria

doi:10.1080/00986445.2018.1555531

Cited by 5 publications

(3 citation statements)

References 73 publications

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“…ANFIS is equivalent to FIS. 37 FIS is divided into three main groups: Mamdani, Sugeno, and Tsukamato. 38 ANFIS performance is highly determined by design of membership functions which is basic structure of fuzzy systems.…”

Section: Anfismentioning

confidence: 99%

Pull‐out capacity prediction of sustainable cementitious composites with artificial intelligence and statistical methods

Ünsalan

Bankır

Cansız

2023

Structural Concrete

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Concrete is used with reinforcement in structures so adherence gains importance especially in fire scenarios. To contribute production of sustainable concrete, by-products like granulated blast furnace slag, fly ash, and silica fume were used, generally. In this study, to determine the elevated temperature resistance of by-product-added composites, samples were exposed to 250, 500, and 750 C and bonding behavior of composites was determined with pull-out test. Moreover, prediction models were developed to estimate concrete-reinforcement adherence values without experimentation and importantly before a fire. For the prediction models, considering the cross correlation, the mixture type, temperature, compressive strength, and flexural strength of concretes were selected as independent variables different from literature and pull-out capacity (POC) as dependent variable. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were used for prediction models. As a statistical method, multiple linear regression was used. The performances of pull out prediction models were compared according to coefficient of correlation (R), mean square error (MSE), and mean percentage error (MPE). Among the statistical models, Quadratic and pure quadratic performance surpassed the ANFIS model, which is a combination of ANN and fuzzy techniques. The best performance was obtained in ANN model with 99.85%, 3.65 kg, 3.1% for R, MSE and MPE, respectively. Therefore, ANN can provide a new applicable model to effectively predict POC of by-product-added cementituous composites under fire effect.

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Section: Anfismentioning

confidence: 99%

Pull‐out capacity prediction of sustainable cementitious composites with artificial intelligence and statistical methods

Ünsalan

Bankır

Cansız

2023

Structural Concrete

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“…Since these wastes are stable in various conditions, they sometimes stay unchanged in soil and water for many years and cause various complications. Different methods like adsorption [2,3], photodegradation [4,5], separation [6,7], bioand chemical degradation [8,9], coagulation [10,11], filtration [12,13], ultrasonication [14][15][16], etc. are implemented to fully ensure the purity of the water used for drinking or irrigation.…”

Section: Introductionmentioning

confidence: 99%

SYNTHESIS OF ZnAl-LDH/PVA NANOCOMPOSITE AND ADSORPTION OF PATENT BLUE V FOOD DYE FROM WATER SOLUTION

Balayeva¹,

Azizov²,

Muradov³

et al. 2023

AChJ

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In the presented research work, zinc and aluminum containing layered double hydroxides on the polyvinyl alcohol matrix (ZnAl LDH/PVA) were prepared by the co-formation technique and characterized by X-ray diffractometer, Brunauer-Emmett-Teller (BET) and Ultraviolet-visible (UV-Vis) spectroscopy. Both low and high pH is determined as optimal pH for Patent Blue V (PBV) adsorption on the ZnAl LDH/PVA nanocomposite and it is explained by the fact that the dye molecule is zwitterionic. Sorption of Patent Blue V food additive (E 131) on the obtained nanocomposite was studied by Temkin, Freundlich, Langmuir, and Dubinin-Radushkevich (D-R) isotherm models. Based on the obtained isotherm curves, the adsorption of PBV more closely matches Temkin model. The regenerated nanocomposite shows higher adsorption because the specific surface area increased from 5m2 g-1 to 8.94 m2 g-1 by BET analysis

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“…Based on these characteristic properties, this compound poses considerable threats to the environment and consequently needs to be treated in an effective manner [9]. Treatment techniques, including coagulation-flocculation, membrane separation, reverse osmosis (RO), and solvent extraction, have been applied to process these problematic effluents [10].…”

Section: Introductionmentioning

confidence: 99%

Active Carbon from Microwave Date Stones for Toxic Dye Removal: Setting the Design Capacity

Hijab

Parthasarathy

et al. 2020

Chem Eng & Technol

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The widely used toxic dye malachite green (MG) poses a significant risk to human health, having a mutagenic effect. Waste date stones were used to produce microwave‐activated carbons and were applied to adsorb the highly toxic dye. The critically important task of selecting the correct design adsorption capacity for different effluent pollutant concentrations to meet effluent discharge limit standards is described and a novel design selection criteria approach is presented.

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Application of adaptive neuro-fuzzy interference system on biosorption of malachite green using fir (Abies nordmanniana) cones biomass

Cited by 5 publications

References 73 publications

Pull‐out capacity prediction of sustainable cementitious composites with artificial intelligence and statistical methods

Pull‐out capacity prediction of sustainable cementitious composites with artificial intelligence and statistical methods

SYNTHESIS OF ZnAl-LDH/PVA NANOCOMPOSITE AND ADSORPTION OF PATENT BLUE V FOOD DYE FROM WATER SOLUTION

Active Carbon from Microwave Date Stones for Toxic Dye Removal: Setting the Design Capacity

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