Use of triangular membership function for prediction of compressive strength of concrete containing nanosilica

Gupta, Sakshi

doi:10.1080/23311916.2015.1025578

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…A convergência das predições pode ser visualizada por meio do parâmetro R² na Figura 6. Os maiores valores de divergência relativa foram encontrados ao simular os dados de Hatem et al (2012), Gupta (2015) e Ahmed et al (2016). Essa divergência pode ser devida às diferentes características dos concretos adotados nas distintas pesquisas.…”

Section: Resultados Anfisunclassified

Modelo neuro-fuzzy para predição do aporte de energia de diferentes dosagens de concreto em edificações

2021

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Resumo Com o aumento do processo de urbanização e da população das cidades, surge a necessidade de entender o custo energético para produção dos materiais de construção. Entre os instrumentos utilizados, o aporte de energia é um importante instrumento no monitoramento do uso de fontes de energia não renováveis para produção de concretos convencionais, o que demanda novas pesquisas na área. Neste trabalho, um modelo híbrido ANFIS (Adaptive Neuro-Fuzzy Inference System) foi desenvolvido para predição do aporte de energia, para a avaliação da demanda de energia necessária para cada um dos componentes na produção de concretos convencionais (cimento, água, agregado miúdo e agregado graúdo), mediante a utilização de 101 dosagens experimentais, 101 dosagens para validação e coeficientes energéticos disponíveis em literaturas. Identificou-se que a escolha adequada da dosagem pode gerar uma economia no custo energético para produção do concreto da ordem de 24,77%, mantendo a característica mecânica de resistência à compressão para construções convencionais.

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Section: Resultados Anfisunclassified

Modelo neuro-fuzzy para predição do aporte de energia de diferentes dosagens de concreto em edificações

2021

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“…(Dela & Caluyo, 2013) applied Gaussian and exponential MFs for path loss prediction in specific urban areas using ANFIS and the relative error obatined was 0.2303. In a bid to search for most suitable MF, in Table 1, we saw how researchers (Gupta, Sharma, & Sharma, 2014); (Gupta S. , 2015); (Gupta, Verma, & Mehlawat, 2011) Interestingly, among all the contending MFs and across all the studies, the Triangular MF gives the best performance. From table 1, we acknowledged the concerted efforts by researchers in a bid to investigate the effects of the Fuzzy system parameters such as the number and shape of membership functions performance of the model.…”

Section: Review Of Related Workmentioning

confidence: 99%

Effect of Membership Functions and Data Size on the Performance of ANFIS-Based Model for Predicting Path Losses in the VHF and UHF Bands

Surajudeen-Bakinde

Фарук

Abdulkarim

et al. 2021

JER is an international, peer-reviewed journal that publishes f

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This paper investigates the effect of number and shape of membership function (MF), and training data size on the performance of ANFIS model for predicting path losses in the VHF and UHF bands in built-up environments. Path loss propagation measurements were conducted in four cities of Nigeria over the cellular and broadcasting frequencies. A total of 17 broadcast transmission and cellular base stations were utilized for this study. From the results obtained, it can be concluded for the broadcasting bands that the generalized bell MF shows better performance with an average RMSE of 3.00 dB across all the routes, followed by gaussian, Pi, trapezoid and triangular MFs in that other with average RMSE values of 3.09 dB, 3.11 dB, 3.16 dB and 3.23 dB respectively. For the cellular systems, Triangular MF outperformed other MFs with the lowest average RMSE. The generalized bell MF was found to be suited for WCDMA band while triangular MF is most suited for GSM band. Furthermore, it can also be concluded that the higher the number of membership functions, the lower the RMSE, whereas, a decrease in the data size leads to a reduction in the RMSE values. The findings of this study would help researchers and network planners to make a more informed decision on choosing appropriate system parameters when modeling ANFIS models for path loss prediction.

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“…LITERATURE REVIEW Sakshi Gupta [7] (2015) predicted partial replacement of cement with nanosilica it increases durability of material. The main aim of the study is to optimise the contents and reduce the cost and efforts.…”

Section: IImentioning

confidence: 99%

A Review on Nano Materials in Cement

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2020

IJRASET

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The research in construction industry nowadays is mainly focusing on the basic science of cement materials at nano level. The research is also continuing to improve the durability and sustainability of concrete and realized significant increase in strength of material by incorporating nanoparticles. The review paper summarises the effect of various nanoparticles addition on the strength material. It provides the current development of application of nano-materials in mortar and concrete. Nano material can assist in intensifying the use of resources and get the required properties by reducing the use of resources. This review paper also addresses the current development regarding use of nanomaterial in construction industry. The paper first presents general information, then focuses on the most effective nano additives such as nano silica, nano-titania dioxide, iron oxides, chromium oxide, nanoclay are summarized. Along with benefits, some health risks are also associated with the use of nanotechnology. The risks are can be remedied so that the nano building products could be fully exploited for the benefits of mankind.

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Use of triangular membership function for prediction of compressive strength of concrete containing nanosilica

Cited by 14 publications

References 20 publications

Modelo neuro-fuzzy para predição do aporte de energia de diferentes dosagens de concreto em edificações

Modelo neuro-fuzzy para predição do aporte de energia de diferentes dosagens de concreto em edificações

Effect of Membership Functions and Data Size on the Performance of ANFIS-Based Model for Predicting Path Losses in the VHF and UHF Bands

A Review on Nano Materials in Cement

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