Two ways to save (on) gas you probably don’t know about!

With rising gas prices and rising environmental concerns, gas efficiency is on everyone’s mind these days, with automobile industries designing engines that give more and more mileage per gallon and consumers looking for ways to use those engines in the best, more economical way possible.

Are the usual energy efficiency solutions coming to their natural end?

As smart meters and their applications are becoming more and more commonplace among residential, commercial and industrial consumers alike, the question of how much more efficiency they can secure for building owners and businesses becomes all the more pressing: do retrofits, upgrades and the obvious energy management tweaks mark an efficiency “ceiling”, or is there another way to lower consumption and lower energy bills?

The less the merrier: dimensionality reduction and knowledge discovery

An increasing number of contemporary applications produce massive volumes of very high dimensional data. In scientific databases, for example, it is common to encounter large sets of observations, represented by hundreds or even thousands of variables. Typical cases include astronomical, energy and network applications. In order to extract knowledge from these datasets, we need to access the underlying, hidden information.

3 key factors of behavioral-based learning systems that contribute to user’s engagement

There has been raging interest in treating knowledge as a significant organizational asset due to the fact that it provides a sustainable competitive advantage; only during the last few years truly innovative and disruptive KMSs have been proposed. This is especially due to the rise of the Internet and other technological advances that facilitate the development of these systems.

Energy consumption modeling through an artificial intelligence approach

One of the most important aspects of power systems is electricity demand forecasting. Load forecasting can be long-term, mid-term and short-term. Long-term forecasts of the peak electricity demand are required for capacity planning and maintenance scheduling. Medium-term demand forecasts are important for power system operation and planning. Short-term load forecasts are needed for the control and scheduling of power systems.