Graph-based algorithms for comparison and prediction of household-level energy use profiles

We present an efficient graph-based algorithm for quantifying the similarity of household-level energy use profiles, using a notion of similarity that allows for small time–shifts when comparing profiles. Experimental results on a real smart meter data set demonstrate that in cases of practical interest our technique is far faster than the existing method for computing the same similarity measure. Having a fast algorithm for measuring profile similarity improves the efficiency of tasks such as clustering of customers and cross-validation of forecasting methods using historical data. Furthermore, we apply a generalisation of our algorithm to produce substantially better household-level energy use forecasts from historical smart meter data.

The origins of small wars: from special operations to ideological insurgencies

This edited volume explores the origins of the term small wars and traces it to special operations. In the 17th century, such "guerrilla/petite guerre" special operations grew out of training and winter operations of the regular forces as practiced in the 16th century. In the 18th century, they fused with a tradition going back to Antiquity, of employing special ethnic groups (such as the Hungarian Hussars) for special operations. Side by side with these special operations, however, there was the even older genealogy of uprisings and insurgencies, which since the Spanish Guerrilla of 1808-1812 has been associated with this term. All three traditions have influenced each other.

The iso-Score Curve Graph. A new tool for competitive bidding

The present work describes a new tool that helps bidders improve their competitive bidding strategies. This new tool consists of an easy-to-use graphical tool that allows the use of more complex decision analysis tools in the field of Competitive Bidding. The graphic tool described here tries to move away from previous bidding models which attempt to describe the result of an auction or a tender process by means of studying each possible bidder with probability density functions. As an illustration, the tool is applied to three practical cases. Theoretical and practical conclusions on the great potential breadth of application of the tool are also presented.