Araştırma Çıktıları

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Browsing Araştırma Çıktıları by Publisher "ACAD SCIENCES CZECH REPUBLIC, INST COMPUTER SCIENCE"

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    PublicationOpen Access
    A NEW MULTILAYER FEEDFORWARD NETWORK BASED ON TRIMMED MEAN NEURON MODEL
    (ACAD SCIENCES CZECH REPUBLIC, INST COMPUTER SCIENCE, 2015) Yolcu, Ufuk; Bas, Eren; Egrioglu, Erol; Aladag, Cagdas Hakan
    The multilayer perceptron model has been suggested as an alternative to conventional approaches, and can accurately forecast time series. Additionally, several novel artificial neural network models have been proposed as alternatives to the multilayer perceptron model, which have used (for example) the generalized mean, geometric mean, and multiplicative neuron models. Although all of these artificial neural network models can produce successful forecasts, their aggregation functions mean that they are negatively affected by outliers. In this study, we propose a new multilayer, feed forward neural network model, which is a robust model that uses the trimmed mean neuron model. Its aggregation function does not depend on outliers. We trained this multilayer, feed forward neural network using modified particle swarm optimization. We applied the proposed method to three well-known time series, and our results suggest that it produces superior forecasts when compared with similar methods.
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    PublicationOpen Access
    AN INTELLIGENT SOFTWARE MODEL DESIGN FOR ESTIMATING DEPOSIT BANKS PROFITABILITY WITH SOFT COMPUTING TECHNIQUES
    (ACAD SCIENCES CZECH REPUBLIC, INST COMPUTER SCIENCE, 2015) Sonmez, F.; Bulbul, S.
    Profitability of Turkish banking sector gained importance after national and international financial crisis happened in the last decade, which revealed the need to make a research on profitability and the factors determining profitability. In recent years, new techniques of soft computing (SC) like genetic algorithms (GAs), fuzzy logic (FL) and especially artificial neural networks (ANNs) have been applied into the financial domain to solve the domain issues because of their successful applications in nonlinear multivariate situations. An adaptive system was needed due to the fact that insufficient use of application software programs for SC and the fact that single software is only applicable for specific model. Furthermore, even though ANNs have been applied to many areas; little attention has been paid to estimation of bank profitability with ANNs. This article is intended to analyze and estimate the profitability of deposit banks in Turkey with an adaptive software model of ANNs which have not been previously applied for this context, comprehensively. The results from the software model, which processes the factors affecting profitability, indicate that all of the variables used have significant impacts in varying proportions on profitability and that obtained estimations achieved the targeted and acceptable performance of success. This software model is expected to provide easiness on estimating bank profitability, since giving successful estimations and not being affected by user differences. Additionally, it is aimed to construct a software model for being used in different fields of study and financial domain.