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Physics-informed neural networks (PINNs) have emerged as an effective technique for solving PDEs in a wide range of domains. Recent research has demonstrated, however, that the performance of PINNs ca...
This talk focuses on the even-triggered cooperative control problem of heterogeneous multi-agent systems (MASs) using data-based reinforcement learning (RL) algorithm. To lower the communication and c...
The 2017 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2017) will be held in Ljubljana (Slovenia), a beautiful medieval town. Ljubljana lies halfway between Vienna and Venice, at ...
Some problems of complex systems are internal to the system whereas other problems exist peripherally; two such problems will be explored in this thesis. First, is the issue of excessive jerk from ins...
One of the biggest hurdles to the development of an effective driver state monitor is the that there is no real-time eye-gaze detection. This is primarily due to the fact that such systems require cal...
Abstract: Harmonic theory provides a mathematical framework to describe the structure, behavior, evolution and emergence of harmonic systems. A harmonic system is context aware, contains elements that...
In this study, a simple method based on the adaptive neuro-fuzzy inference system (ANFIS) is presented for computing the association probabilities. The computed association probabilities are used to t...
We propose a modified neuro-adaptive learning fuzzy system that can model, simulate, and analyze dynamic data. The system has two switches and three subsystems, which fits the need of advanced financi...
Generally, control techniques based on multilayer neural networks are used especially in the case of non-linear process and less in case of linear process, because classical control techniques are goo...

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