Geography often serves as at least a partial determinant of economic and cultural characteristics. For example, individuals who live in affluent neighborhoods are likely to come into contact with other individuals who have similar income and education levels, which often tend to be associated with political views and personal interests. However, within electronic social networks (ESNs), geograp...

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based ...

INTRODUCTION Sepsis-induced myopathy and critical illness myopathy (CIM) are possible causes of muscle weakness in intensive care patients. They have been attributed to muscle membrane dysfunction. The aim of this study was to investigate membrane properties in the early stage of experimental sepsis by evaluating muscle excitability. METHODS In total, 20 anesthetized and mechanically ventilat...

We propose the Automatic-differentiated Physics-Informed Echo State Network (API-ESN). The network is constrained by physical equations through reservoir’s exact time-derivative, which computed automatic differentiation. As compared to original Network, accuracy of time-derivative increased up seven orders magnitude. This key in chaotic dynamical systems, where errors grow exponentially time. s...

The echo state network (ESN) is a cutting-edge reservoir computing technique designed to handle time-dependent data, making it highly effective for addressing time series prediction tasks. ESN inherits the more precise design of standard neural networks and relatively simple learning process has strong capacity solving nonlinear problems. It can disseminate low-dimensional information cues high...

Enterprise social networks provide benefits especially for knowledge-intensive work as they enable communication, collaboration and knowledge exchange. These platforms should therefore lead to increased adoption and use by knowledge-intensive workers such as consultants or indeed researchers. Our interest is in ascertaining whether scientific researchers use enterprise social networks as part o...

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 more real-valued time series modeling tasks and performed exceptionally well. Also using ESNs for processing symbolic sequences s...

Prediction occurs in many biological nervous systems e.g. in the cortex [7]. We introduce a method of adapting the recurrent layer dynamics of an echo-state network (ESN) without attempting to train the weights directly. Initially a network is generated that fulfils the echo state liquid state condition. A second network is then trained to predict the next internal state of the system. In simul...

In this report, we developed a new recurrent neural network toolbox, including the recurrent multilayer perceptron structure and its companying extended Kalman filter based training algorithms: BPTT-GEKF and BPTT-DEKF. Besides, we also constructed programs for designing echo state network with single reservoir, together with the offline linear regression based training algorithm. We name this t...

Alarm fatigue caused by false alarms and alerts is an extremely important issue for medical staff in Intensive Care Units. The ability to predict and classify ECG and ABP patient waveforms can potentially help the staff and hospital systems better classify a patient’s waveforms and subsequent alarms. This project approaches this problem by evaluating the effectiveness of different Echo State Ne...