Steady state analysis of a 3-φ SEIG is generally done through mathematical modeling of its equivalent circuit. The impedance model can be reduced in terms of two nonlinear simultaneous equations consisting of unspecified variables as magnetizing reactance Xm and generated frequency F. The steady state performance analysis of SEIG becomes uncomplicated once the values of Xm and F are explicitly ...

This paper presents a new method for power systems performance optimization using Electromagnetic Transients Simulation. In this method, an emtp-type program (PSCAD/EMTDC) becomes the inner objective function calculation loop of a non-linear optimization program. The procedure is conducted in a Graphical Environment and with the use of specially designed blocks, allows for the selection of any ...

The optimization of a controlled flapping wing micro aerial vehicle for energy-efficient flight in gust using a general, service-oriented framework is investigated. Kinematic (wing-stroke pattern), geometric (wing shape), frequency, and control (state penalty) design variables are considered in a sequence of optimization problems. The service-oriented framework is applied to the integration of ...

This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lowerd...

This paper provides algorithms for predicting the size of the Expanded Search Tree (EST ) of Depthfirst Branch and Bound algorithms (DFBnB) for optimization tasks. The prediction algorithm is implemented and evaluated in the context of solving combinatorial optimization problems over graphical models such as Bayesian and Markov networks. Our methods extend to DFBnB the approaches provided by Kn...

This article presents GraphSLAM, a unifying algorithm for the offline SLAM problem. GraphSLAM is closely related to a recent sequence of research papers on applying optimization techniques to SLAM problems. It transforms the SLAM posterior into a graphical network, representing the log-likelihood of the data. It then reduces this graph using variable elimination techniques, arriving at a lowerd...

Graphical Contents

In reality there are many relational datasets in which both features of instances and the relationships among the instances are recorded, such as hyperlinked web pages, scientific literature with citations, and social networks. Collective classification has been widely used to classify a group of related instances simultaneously. Recently there have been several studies on statistical relationa...