Meta fuzzy functions: Application of recurrent type-1 fuzzy functions

Tak, Nihat

doi:10.1016/j.asoc.2018.08.009

Cited by 23 publications

(10 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bacani [17] developed a fuzzy inference framework, based on the fuzzy relationship, for predicting the temperature and humidity of a greenhouse for Brazilian coffee crops and validated the model's performance in terms of the MAPE metric. Tak [18] proposed a meta-fuzzy function based on the FCM clustering method and confirmed the model's performance using the MAPE metric. Carvalho [19] proposed a hybrid method that combines classical time series modeling and fuzzy set theory to improve the performance of the predictive algorithm and confirmed the performance of the model using the MAPE metric.…”

Section: Of 17mentioning

confidence: 88%

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Yeom

Kwak

2019

Symmetry

View full text Add to dashboard Cite

The predictive performance of different granular models (GMs) was compared and analyzed for methods that evenly divide linguistic context in information granulation-based GMs and perform flexible partitioning. GMs are defined by input and output space information transformations using context-based fuzzy C-means clustering. The input space information transformation is directly induced by the output space context. Usually, the output space context is evenly divided. In this paper, the linguistic context was flexibly divided by stochastically distributing data in the output space. Unlike most fuzzy models, this GM yielded information segmentation. Their performance is usually evaluated using the root mean square error, which utilizes the difference between the model’s output and ground truth. However, this is inadequate for the performance evaluation of information innovation-based GMs. Thus, the GM performance was compared and analyzed using the linguistic context partitioning by selecting the appropriate performance evaluation method for the GM. The method was augmented by the coverage and specificity of the GMs output as the performance index. For the GM validation, its performance was compared and analyzed using the auto MPG dataset. The GM with flexible partitioning of linguistic context performed better. Performance evaluation using the coverage and specificity of the membership function was validated.

show abstract

Section: Of 17mentioning

confidence: 88%

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Yeom

Kwak

2019

Symmetry

View full text Add to dashboard Cite

show abstract

“…Tak et al (2018) proposed a recurrent type fuzzy regression function. Tak (2018) proposed the meta fuzzy functions method. The algorithm for the fuzzy regression functions approach is given below step by step.…”

Section: Fuzzy C Means Methodmentioning

confidence: 99%

Monthly Average Wind Speed Forecasting in Giresun Province with Fuzzy Regression Functions Approach

YILDIRIM¹,

Baş²

2022

Journal of Anatolian Environmental and Animal Sciences

View full text Add to dashboard Cite

show abstract

“…4.1 | The proposed method for dating currency crises Tak (2018) proposed meta fuzzy functions that have been used to aggregate the different methods for a purpose to improve the prediction accuracy. Meta fuzzy index functions (Tak, 2020), later, was introduced as a way of aggregating the information of different indices.…”

Section: Methodsmentioning

confidence: 99%

Dating currency crises and designing early warning systems: Meta‐possibilistic fuzzy index functions

Tak

Gök

2020

Int. J Fin Econ

Self Cite

View full text Add to dashboard Cite

In order to analyse the currency crises in Turkey over the period of January 1990 and October 2019, we first dated currency crises with meta‐possibilistic fuzzy index functions. Then, we determined the significant predictors or leading indicators of currency crisis with logistic regression. Finally, we tried to measure and compare the in‐sample and out‐of‐sample performances of our method with an index generated by principal component analysis (PCA). We found that the models using the currency crisis index generated by our method have higher in‐sample and out‐of‐sample performances than the models using the currency crisis index generated by PCA. We concluded that the change in real exchange rate, bank loans over bank deposits, bank reserves over bank assets, growth in foreign reserves, growth in central bank foreign assets, M2 over foreign assets, change in exports, change in imports, industrial production index, M1 growth, M2 growth, foreign reserves over M1, central bank foreign assets over M1 and public sector credit growth are the leading indicators of currency crisis among 20 explanatory variables. As policy implications, we recommend that government and the monetary authority should strictly monitor the ratio of bank loans over bank deposits, public sector credit growth, the volatility of foreign trade, ratio of foreign reserves and central bank foreign assets over money supply among significant explanatory variables to avoid currency crisis as policy implications.

show abstract

Meta fuzzy functions: Application of recurrent type-1 fuzzy functions

Cited by 23 publications

References 31 publications

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Performance Evaluation of Automobile Fuel Consumption Using a Fuzzy-Based Granular Model with Coverage and Specificity

Monthly Average Wind Speed Forecasting in Giresun Province with Fuzzy Regression Functions Approach

Dating currency crises and designing early warning systems: Meta‐possibilistic fuzzy index functions

Contact Info

Product

Resources

About