This paper is an attempt to introduce the essence and methodology of Artificial Neural Networks (ANN) in marketing. In order to outline the benefits of their analytical application in marketing management, it is demonstrated how to solve a predictive problem applying one of the most widely used...

Accurate and robust short-term load forecasting plays a significant role in electric power operations. This paper proposes a variant of genetic programming, improved by incorporating semantic awareness in algorithm, to address a short term load forecasting problem. The objective is to...

This study attempts to assess the forecasting accuracy of Support Vector Regression (SVR) with regard to other Artificial Intelligence techniques based on statistical learning. We use two different neural networks and three SVR models that differ by the type of kernel used. We focus on...

By means of Self-Organizing Maps we cluster fourteen European countries according to the most suitable way to model their agents’ expectations. Using the financial crisis of 2008 as a benchmark, we distinguish between those countries that show a progressive anticipation of the crisis and those...

This study attempts to improve the forecasting accuracy of tourism demand by using the existing common trends in tourist arrivals form all visitor markets to a specific destination in a multiple-input multiple-output (MIMO) structure. While most tourism forecasting research focuses on univariate...

This study aims to analyze the effects of data pre-processing on the performance of forecasting based on neural network models. We use three different Artificial Neural Networks techniques to forecast tourist demand: a multi-layer perceptron, a radial basis function and an Elman neural network....

This paper employs a new econometric technique to estimate the core inflation in Turkey measured as the shifting means in levels between 1955 and 2014. Using monthly series, we determine the number of shifts using the BIC, the hv-block cross-validation, the Lin-Teräsvirta parameter constancy...

The objective of this paper is to predict, both in-sample and out-of-sample, the consumer price index (CPI) of the United States (US) economy based on monthly data covering the period of 1980:1-2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonally-adjusted...

The use of non-parametric methodologies, the introduction of non-financial variables, and the development of models geared towards the homogeneous characteristics of corporate sub-populations have recently experienced a surge of interest in the bankruptcy literature. However, no research on...

The artificial neural network (ANN) test of Lee et al. (Journal of Econometrics 56, 269–290, 1993) uses the ability of the ANN activation functions in the hidden layer to detect neglected functionalmisspecification. As the estimation of the ANN model is often quite difficult, LWG...