Most of the compressive wideband spectrum sensing algorithms need to recover spectrum, which require high computational complexity. Recently, a novel algorithm for without recovery (NoR) was proposed. Its complexity is several orders magnitude less than that recovery. However, enabling by structure-constrained assumption sparse NoR may fail. In order expand its scope application while reducing ...

forecasting of municipal waste generation is a critical challenge for decision making and planning,because proper planning and operation of a solid waste management system is intensively affected by municipal solid waste (msw) streams analysis and accurate predictions of solid waste quantities generated. due to dynamic and complexity of solid waste management system, models by artificial intell...

This paper studies three techniques for outliers detection in the context of Wireless Sensor Networks, including a machine learning technique, a Principal Component Analysis-based methodology and an univariate statistics-based approach. The first methodology is based on a Least Squares-Support Vector Machine technique, together with a sliding window learning. A modification to this approach is ...

Predicting the price of electricity is crucial for operation power systems. Short-term forecasting deals with forecasts from an hour to a day ahead. Hourly-ahead offer expected prices market participants before hours. This especially useful effective bidding strategies where amount can be reviewed or changed Nevertheless, many existing models have relatively low prediction accuracy. Furthermore...