Fuzzy logic model for the prediction of cement compressive strength

Akkurt, Sedat; Tayfur, Gökmen; Can, Sever

doi:10.1016/j.cemconres.2004.01.020

Cited by 188 publications

(111 citation statements)

References 12 publications

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“…Techniques such as artificial neural networks (Kim et al, 2004;Lee, 2003), evolutionary algorithms (Jayarama et al, 2009;Nazari, 2013;Tsai and Lin, 2011), fuzzy sets and systems (Bohlooli et al, 2012;Demir, 2005), hybrid systems (Akkurt et al, 2004;Reza et al, 2013) are just a few ex-amples among others.…”

Section: Research Significancementioning

confidence: 99%

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

Castro

Carvalho

Ribeiro

et al. 2014

Journal of Cleaner Production

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A b s t r a c tIn this study, efforts were made in order to put forward an integrated recycling approach for the ther-moset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer com-posite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systemat-ically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite.Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability.Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

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Section: Research Significancementioning

confidence: 99%

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

Castro

Carvalho

Ribeiro

et al. 2014

Journal of Cleaner Production

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“…The fuzzy model could have produced lower percentage errors than 5.85% (RMSE 6.94) when constructed with more than 2 input parameters. (Akkurt et al 2004). Fuzzy logic is associated with the human thoughts in generating verbal fuzzy rules.…”

Section: Resultsmentioning

confidence: 99%

“…Fuzzy logic method is suited to systems that require the ability to handle uncertainties (Pham et al 2005). Fuzzy approach is more suitable for the data associated with some error (Akkurt et al 2004). Fuzzy logic can be defined as a mathematical model to study and define uncertainties (Cengiz kayacan et al 2004).…”

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confidence: 99%

Spreadsheet aided fuzzy model for prediction of chapati making quality

Gangadharappa

Prabhasankar

2011

J Food Sci Technol

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A spreadsheet aided fuzzy logic model for predicting chapati making quality characteristics of Indian wheat varieties was created. Data collected from 19 randomly selected wheat varieties were used. Starch damage, Farinograph water absorption as input variables and chapati overall score as output variable were fuzzified by the use of excel spreadsheet and defuzzification was carried out using weighted average method. Fuzzy model was compared with the regression model of measured data for its error levels and ease of application. Standard error of estimate of fuzzy model was smaller (1.825) than measured (2.895) chapati quality score regression model.

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“…[24,25]. This shows that system using fuzzy logic and color have a high potential of accuracy in predicting wood density.…”

Section: Fuzzy Modelingmentioning

confidence: 99%

Prediction of Wood Density by Using Red-Green-Blue (RGB) Color and Fuzzy Logic Techniques

Bardak¹,

Bardak²

2017

Journal of Polytechnic

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Prediction of wood density by using redgreen-blue (rgb) color and fuzzy logic techniques Kırmızı-yeşil-mavi (kym) renk ve bulanık mantık teknikleri kullanılarak odun yoğunluğu tahmini Yazar(lar) (Author(s)): Timuçin BARDAK, Selahattin BARDAKBu makaleye şu şekilde atıfta bulunabilirsiniz(To cite to this article): Bardak T., and Bardak S., "Prediction of wood density by using red-green-blue (rgb) color and fuzzy logic techniques", Politeknik Dergisi, 20(4): 979-984, (2017). Politeknik Dergisi, 2017; 20 (4) : 979-984 Journal of Polytechnic, 2017; 20 (4) : 979-984 ABSTRACTDensity is an important wood property since it correlates to mechanical properties of wood. Fuzzy logic, among the various available Artificial Intelligence techniques, emerges as a good technique in predicting. Digital image analysis is an powerful tool to obtain meaningful data out of an image. In this study, digital image processing based on a red-green-blue (RGB) color examination was practiced to measure the intensity of wood color. Densities of the test samples were measured. Then, a new fuzzy logic model was developed based on these measured values and RGB color intensity of wood. Afterwards, the experimental and modeling data results were compared. 98.17% accuracy was observed between the measurement and the fuzzy logic model. Consequently, Fuzzy logic is visable method for the prediction of the wood density. Keywords

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Fuzzy logic model for the prediction of cement compressive strength

Cited by 188 publications

References 12 publications

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

Spreadsheet aided fuzzy model for prediction of chapati making quality

Prediction of Wood Density by Using Red-Green-Blue (RGB) Color and Fuzzy Logic Techniques

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