The identification of distinct user roles is an important theme in social media research. However, for Enterprise Social Networks (ESN), the use of social media within organisations, research identifying such roles is still lacking. Yet, understanding user roles, in particular regarding their knowledge contributions and communication behaviour, might usefully support companies in managing criti...

The paper discusses methods, forms and safety issues of social network usage for school students. Taking into consideration the growing interest of students to electronic communication in social networks (ESN), it was described their place in the information educational environment. There were made the classification of objects and use of ESN to help teachers and school authority to teach stude...

This work proposes the design of Environmental Sensor Networks (ESN) through balancing robustness and redundancy. An Evolutionary Algorithm (EA) is employed to find the optimal placement of sensor nodes in the Region of Interest (RoI). Data quality issues are introduced to simulate their impact on the performance of the ESN. Spatial Regression Test (SRT) is also utilised to promote robustness i...

Modeling the dynamics of formation and evolution protostellar disks as well history stellar mass accretion typically involve numerical solution complex systems coupled differential equations. The resulting protostars is known to be highly episodic due recurrent instabilities also exhibits short timescale flickering. By leveraging strong predictive abilities neural networks, we extract some crit...

The uncertainty and regularity of wind power generation are caused by wind resources’ intermittent and randomness. Such volatility brings severe challenges to the wind power grid. The requirements for ultrashort-term and short-term wind power forecasting with high prediction accuracy of the model used, have great significance for reducing the phenomenon of abandoned wind power , optimizing the ...

With deregulation and growth of the power industry, many power system elements such as generators, transmission lines, are driven to operate near their maximum capacity, especially those serving heavy load centres. Wide Area Controllers (WACs) using wide area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system st...

Echo State Networks (ESN) have been used successfully in a broad range of applications, from dynamic pattern recognition to channel equalization in digital communication systems [5, 7, 9]. Their simplicity and ease of use, paired with their underlying ”mathematical power” make them an ideal choice in many black-box modelling tasks. For many applications, however, it is mandatory to learn and ad...

We propose an EEG classification algorithm for the mental task BCI paradigm that uses Echo State Networks (ESN). In this approach, ESN are used to model the dynamics of EEG during each of several mental tasks. Classification is performed by applying several of these models and assigning the class label associated with the ESN that produces the lowest forecasting error. Experiments performed on ...

A lot of attention is now being focused on connectionist models known under the name “reservoir computing”. The most prominent example of these approaches is a recurrent neural network architecture called an echo state network (ESN). ESNs were successfully applied in several time series modeling tasks and according to the authors they performed exceptionally well. Multiple enhancements to stand...

As an efficient recurrent neural network (RNN) model, reservoir computing (RC) models, such as Echo State Networks, have attracted widespread attention in the last decade. However, while they have had great success with time series data [1], [2], many time series have a multiscale structure, which a single-hidden-layer RC model may have difficulty capturing. In this paper, we propose a novel hi...