Renewable electrical energy grid connection is
hampered by transmission capacity limitations and public
opposition to new transmission development. This paper
presents a methodology to find the optimal positions on ...
Background:
Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, ...
Network modeling can be approached using either discriminative or probabilistic
models. In the task of link prediction a probabilistic model will give a probability
for the existence of a link; while in some scenarios ...
In the scope of a recently launched European Research Project, a team of experts from public laboratories and TSO is in charge of defining the concepts and methodological approaches to design and analyse the technical and ...
Many countries have declared future renewable
energy penetration targets. Wind power connection to power systems is delayed by limited transmission system capacity as attractive wind sites are often located in weakly ...
To assess the safety of an existing bridge, the loads to which it may be subject in its
lifetime are required. Statistical analysis is used to extrapolate a sample of load effect values from the simulation period to the ...
More accurate assessment of safety can prevent unnecessary repair or replacement of existing bridges which in turn can result in great cost savings at network level. The allowance for dynamics is a significant component ...
The mechanistic empirical method of flexible pavement design/assessment uses a large number of numerical truck model runs to predict a history of dynamic load. The pattern of dynamic load distribution along the pavement ...
Assessment of highway bridge safety requires a prediction of the probability of
occurrence of extreme load effects during the remaining life of the structure. While the
assessment of the strength of an existing bridge ...
This paper proposes a new probabilistic classification algorithm using a Markov random field approach. The joint distribution of class labels is explicitly modelled using the distances between feature vectors. Intuitively, ...