Abstract: A mechanism is provided for detecting air-pollution anomalies. A historical air-pollution pattern is identified for each of a plurality of air-pollution monitoring stations. For each of the plurality of air-pollution monitoring stations, responsive to receiving real-time data from a particular air-pollution monitoring station, the real-time data is compared to the historical air-pollution pattern associated with the particular air-pollution monitoring station. A density difference value is generated based on the comparison of the real-time data to the historical air-pollution pattern associated with the particular air-pollution monitoring station and a determination is made as to whether the density difference value is greater than a predetermined confidence threshold.

Abstract: A mechanism is provided for detecting air-pollution anomalies. A historical air-pollution pattern is identified for each of a plurality of air-pollution monitoring stations. For each of the plurality of air-pollution monitoring stations, responsive to receiving real-time data from a particular air-pollution monitoring station, the real-time data is compared to the historical air-pollution pattern associated with the particular air-pollution monitoring station. A density difference value is generated based on the comparison of the real-time data to the historical air-pollution pattern associated with the particular air-pollution monitoring station and a determination is made as to whether the density difference value is greater than a predetermined confidence threshold.

Abstract: A method for predicting the power of a target wind turbine newly added in a wind farm. The method including determining a reference wind turbine associated with the target wind turbine; determining a power curve mapping relationship between the reference wind turbine and the target wind turbine according to a power curve of the reference wind turbine and a power curve of the target wind turbine; obtaining a power data distribution mapping relationship between the reference wind turbine and the target wind turbine according to wind speed historical data of the reference wind turbine and wind speed historical data of the target wind turbine; and estimating the power of the target wind turbine according to the power curve mapping relationship, the power data distribution mapping relationship, as well as the power and wind speed of the reference wind turbine.

Abstract: A system and method of determining at least one location for a retail outlet in a region are described. The system and method use clustering technology for partitioning the region into a fixed number of sub-regions. Then, the system and method compute marginal increments from input data for each sub-region. The system and method choose a sub-region having a maximal marginal increment for a location of a first retail outlet.

Abstract: A system and method of determining at least one location for a retail outlet in a region are described. The system and method use clustering technology for partitioning the region into a fixed number of sub-regions. Then, the system and method compute marginal increments from input data for each sub-region. The system and method choose a sub-region having a maximal marginal increment for a location of a first retail outlet.