Bilimsel çalışmalarda kullanılan bazı yapay zeka uygulamalarının ve trendlerinin incelenmesi

Saplioğlu, Kemal; Uzundurukan, Soner

doi:10.24012/dumf.394591

Cited by 5 publications

(2 citation statements)

References 45 publications

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“…𝑦 = 𝑏 1 𝑥 1 + 𝑏 2 𝑥 2 + ⋯ + 𝑏 𝑛 𝑥 𝑛 + 𝑎 (14) Here; y represents the dependent variable, a the constant number, b the regression coefficients, x the independent variables and n the number of inputs (Saplıoğlu et al 2017).…”

Section: Regression Analysis Methodsmentioning

confidence: 99%

WITHDRAWN: The evaluation of monthly precipitation and average temperature by using innovative graphical and statistical trend approaches: Palu station example

Acar

2023

Preprint

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Climate change occurring worldwide due to global warming affects rainfall, flow, humidity and temperature, etc. in many regions. It has begun to significantly change the regimes of hydro-meteorological parameters. It is extremely important to analyze the future changes of these parameters, which significantly affect the management of water resources, ecosystems and agricultural activities. In this study, the temporal variability of monthly total precipitation (1965–2012) and monthly average temperature (1965–2020) data of Palu station located within the borders of Elazığ province in Turkey was investigated. Mann-Kendall (MK) and Spearman's Rho (SR) test statistics were used to statistically determine the trends of temperature and precipitation data. In addition to these methods, analyzes were carried out with three innovative trend methods that are capable of interpreting trends both statistically and visually. These innovative trend methods are Innovative Polygon Trend Analysis (IPTA), Innovative Şen Test (Şen-ITA) and trend analysis with the combination of Wilcoxon test and scatter diagram (CWTSD). In addition, precipitation and temperature data were subjected to regression analysis separately and sets of equations were obtained and the decrease-increase amounts were determined in mm and ⸰C. In particular, the IPTA method was applied separately for the arithmetic mean and standard deviation, and the transitions between the increasing and decreasing regions of the trends on a monthly basis were determined and the slopes and lengths of the trends resulting from these transitions were calculated. With the application of the IPTA method, an increasing trend in some months and a decreasing trend in other months were detected for the two parameters. In addition, when the results of precipitation and temperature data were examined, it was seen that there was no single or regular polygon in the IPTA graphs, so both parameters varied over the years and did not exhibit a homogeneous behavior. In the MK test, SR test, Wilcoxon test statistics, Şen-ITA and NO-ITA methods, apart from some months in which increasing and decreasing trends were detected, months in which no trend could be detected, that is, there was no trend, were also observed. When the results obtained from the analysis of two parameters from the relatively new CWTSD method are examined, they show strong consistency with the results of the MK test, SR test and Şen-ITA methods. Advantages such as performing numerical and visual trend analysis with the CWTSD method and determining the trends of data with low-medium-high values have shown that this method can be used as an alternative to the MK test, SR test and Şen-ITA methods that are widely used in the literature. Finally, the IPTA method was evaluated to be more sensitive in determining trends on a monthly basis compared to other methods used in the study..

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Section: Regression Analysis Methodsmentioning

confidence: 99%

WITHDRAWN: The evaluation of monthly precipitation and average temperature by using innovative graphical and statistical trend approaches: Palu station example

Acar

2023

Preprint

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“…The applications of artificial intelligence algorithms in the field of engineering are increasing day by day [15,16]. In this study, an adaptive neuro-fuzzy inference system (ANFIS) of artificial intelligence algorithms was preferred.…”

Section: Adaptive Neuro-fuzzy Inference System (Anfis)mentioning

confidence: 99%

Cam Fiberle Güçlendirilmiş Killi Zeminin Kayma Mukavemetinin Uyarlamalı Ağ Tabanlı Bulanık Çıkarım Sistemi (ANFIS) ile Tahmini

Sungur

Yazici

Keskin

2022

ECJSE

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In recent years, the use of artificial intelligence algorithms in geotechnical engineering has increased, and successful results have been obtained in geotechnical engineering using artificial intelligence algorithms. The objective of this study is to estimate the shear strength of glass fiber reinforced clay soil using ANFIS. For this purpose, specimens with different water contents (13%, 15% and 17%) and different glass fiber addition ratios (0%, 1%, 1.5% and 2%) were prepared. The ANFIS models were created using the shear strength (τ) data obtained by direct shear tests on the prepared specimens. To create the best fitting ANFIS model in the current study, 75%, 77%, 80%, and 83% of the data for training and 25%, 23%, 20%, and 17% of the data for testing were used, respectively. However, to estimate the shear strength in each ANFIS model, the normal stress (σ), glass fiber content (Fc), and water content (ω) are considered as input parameters. Statistical parameters such as root mean square error (RMSE), regression coefficient (R2), root square error (RSE), and mean absolute error (MAE) were also calculated to determine the success rates of the ANFIS models. Examination of the statistical parameters revealed that the data used 80% for training and 20% for testing provided the best results in estimating the shear strength of the ANFIS model.

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A Study on the Adoption of the Artificial Intelligence Product Virtual Influencer on Instagram in the Context of the Spread of Innovations by Followers

Garip

Inceli

2021

Erciyes İletişim Dergisi

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Large companies use AI product virtual influencers as a marketing tool to make a profit. It is noteworthy that virtual influencers operate on Instagram, the photo-sharing network. This research discussed how Instagram users perceive the virtual influencer which is created by artificial intelligence in the perspective of the diffusion of innovations. It also focused on the direction of the comments made by Instagram users. The research is structured according to the case study within the scope of qualitative research. The following research questions are addressed in this article: "How do Instagram users perceive the shares of the A.I. virtual influencer? What is the direction of the comments made by Instagram users who follow the A.I. virtual influencer?" The obtained data were analyzed by qualitative and quantitative content analysis methods. According to the results of the analysis, it has been observed that Instagram users tend to accept the virtual influencer seen as an innovation. At the same time, it was noted that the tendency to accept leads to purchasing behavior.

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Bilimsel çalışmalarda kullanılan bazı yapay zeka uygulamalarının ve trendlerinin incelenmesi

Cited by 5 publications

References 45 publications

WITHDRAWN: The evaluation of monthly precipitation and average temperature by using innovative graphical and statistical trend approaches: Palu station example

WITHDRAWN: The evaluation of monthly precipitation and average temperature by using innovative graphical and statistical trend approaches: Palu station example

Cam Fiberle Güçlendirilmiş Killi Zeminin Kayma Mukavemetinin Uyarlamalı Ağ Tabanlı Bulanık Çıkarım Sistemi (ANFIS) ile Tahmini

A Study on the Adoption of the Artificial Intelligence Product Virtual Influencer on Instagram in the Context of the Spread of Innovations by Followers

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