A method for an intelligent handover decision mechanism among different radio access networks where the available network set is obtained dynamically at the mobile client comprises four steps as explained by the flow chart in Figure3.
In order to illustrate the application of the framework in practice, the paper presents a method based on the framework and the results from applying that method for twelve intelligent vehicle systems in Europe.
We propose an extension of ANEMONA, a multi-agent based method for engineering intelligent manufacturing systems, in order to integrate and take into account NDT for maintenance during the development process.
This paper presents a new method for the intelligent online management of both active and reactive power of a BESS based on a radial basis function neural network (RBFNN) incorporating particle swarm optimization (PSO) to prevent the stand-alone microgrid from instability and system collapse.
Results of experiments demonstrate that the proposed method is effective for intelligent systems for solving various tasks autonomously in a real environment.
A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data.
