There are different causes for vacancies in the housing market. The scientific literature provides a series of … economics. Concerning the latter, a new theoretical framework is used in order to explain vacancies in the housing market in the …

-family residential sector. In this paper, we build a sensor-based forecasting model using Support Vector Regression (SVR), a commonly …. Ultimately, accurate and cost effective wide-scale energy prediction is a vital step towards next-generation energy efficiency …

-mean-square error) and the coefficient of determination (R2). The prediction results of SVR–POLY models outperformed the results of SVR …–RBF models for all prediction horizons and all sampling intervals. Moreover, the SVR–POLY demonstrated high generalization … potential domains is control, where short-term prediction of heat load can play a significant role. With reliable prediction of …

Prediction of stock prices is an issue of interest to financial markets. Many prediction techniques have been reported …

prediction of rock burst classification with case instances using cloud models and attribution weight. First, cloud models are … and applicable for prediction of rock burst classification. Finally, different models with varying indicators are …

Prediction is very important in business planning. The ability to accurately predict the future is fundamental to many …