On the Political Aspects of Unemployment: The Case of Election Results

Unemployment is related to economic, political and social aspects. One of the least analysed political aspects is the relationship that, from a partisan or ideological perspective, should exist between the election results and the aging level of the voters, which is to be reflected in different electoral costs of unemployment. This chapter updates previous work on the subject, using a spatial econometrics methodology to estimate the relationship between the levels of aging and the election results that were obtained in the most recent elections that took place in Portugal, i.e. the October 2015 legislative elections. The results confirm the hypothesis that the level of unemployment involves a higher (resp. lower) electoral cost the less (resp. more) aged is the electorate.

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models.