In this paper, prediction of signal power in Code Division Multiple Access (CDMA) systems in urban radio channels is investigated. We focus on the processing of the measured input signal for power control purposes in a mobile station receiver. Predictive filtering based on a polynomial signal model is proposed, and a class of FIR-type polynomial filters is investigated with simulations. Two al...

Wind energy is a promising alternative source of clean and renewable that can help mitigate climate change. Accurate prediction power generation in wind turbines critical for the effective integration into grid. In this study, we compare performance two popular machine learning algorithms, linear regression random forest, turbines. We use speed direction as input variables output variable. Our ...

Connecting wind power to the power grid has recently become more common. To better manage and use wind power, its strength must be predicted precisely, which is of great safety and economic significance. In this paper, the short-term power prediction of wind power is based on self-adaptive niche particle swarm optimization (NPSO) in a neural net. Improved PSO adopts the rules of classification ...

Bankruptcy is an event with strong impacts on management, shareholders, employees, creditors, customers and other stakeholders, so as bankruptcy challenges the country both socially and economically. Therefore, correct prediction of bankruptcy is of high importance in the financial world. This research intends to investigate financial crisis prediction power using models based on Neural Network...

Despite the clean and renewable advantages of solar energy, instability photovoltaic power generation limits its wide applicability. In order to ensure stable power-grid operations safe dispatching grid, it is necessary develop a model that can accurately predict generation. As widely used prediction method, stacking has been applied in many fields. However, few studies have models research, we...