This study proposes a hybrid forecasting approach that consists of the EWT (Empirical Wavelet Transform), CSA (Coupled Simulated Annealing) and LSSVM (Least Square Support Vector Machine) for enhancing the accuracy of short-term wind speed forecasting. The EWT is employed to extract true...

Forecasting of wind speed and wind power generation is indispensible for the effective operation of a wind farm, and the optimal management of its revenue and risks. Hybrid forecasting of time series data is considered to be a potentially viable alternative compared with the conventional single...

Entre los factores determinantes de la actuación exportadora de las empresas, numerosos estudios han subrayado la relevancia del mix de marketing. Generalmente, la mayoría de los estudios abordan el análisis de las variables centrado en estrategias específicas, en particular fenómenos de...

This paper presents slope stability evaluation and prediction with the approach of a fast robust neural network named the extreme learning machine (ELM). The circular failure mechanism of a slope is formulated based on its material, geometrical and environmental parameters such as the unit...

The level of default in financial institutions is a key piece of information in the activity of these organizations and reveals their level of risk. This in turn explains the growing attention given to variables of this kind, during the crisis of these last years. This paper presents a method to...

In this paper, an M–EEMD–ELM model (modified ensemble empirical mode decomposition (EEMD)-based extreme learning machine (ELM) ensemble learning paradigm) is proposed for landslide displacement prediction. The nonlinear original surface displacement deformation monitoring time series of...

Wind energy is the fastest growing renewable energy technology. Wind turbines do not produce any form of pollution and when strategically placed, it naturally blends with the natural landscape. In the long run, the cost of electricity using wind turbines is cheaper than conventional power plants...

Weather derivatives provide a tool for weather risk management, and the markets for these exotic financial products are gradually emerging in size and importance. This unique monograph presents a unified approach to the modeling and analysis of such weather derivatives, including financial...

Reliable wind modelling is of crucial importance for wind farm development. The common practice of using sector-wise Weibull distributions has been found inappropriate for wind farm layout optimization. In this study, we propose a simple and easily implementable method to construct joint...

A trivariate maximum entropy distribution of significant wave height, wind speed and the relative direction is proposed here. In this joint distribution, all the marginal variables follow modified maximum entropy distributions, and they are combined by a correlation coefficient matrix based on...