Abstract: A power cable is widely used for power supply in
power distributing networks and power transmission lines. Due to
limitations in the production, delivery and setting up power cables,
they are produced and delivered in several separate lengths. Cable
itself, consists of two cable terminations and arbitrary number of
cable joints, depending on the cable route length. Electrical stress
control is needed to prevent a dielectric breakdown at the end of the
insulation shield in both the air and cable insulation. Reliability of
cable joint depends on its materials, design, installation and operating
environment. The paper describes design and performance results for
new modeled cable joints. Design concepts, based on numerical
calculations, must be correct. An Equivalent Electrodes
Method/Boundary Elements Method-hybrid approach that allows
electromagnetic field calculations in multilayer dielectric media,
including inhomogeneous regions, is presented.
Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.