Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles

S Chen, J Dong, P Ha, Y Li… - Computer‐Aided Civil and …, 2021 - Wiley Online Library
A connected autonomous vehicle (CAV) network can be defined as a set of connected
vehicles including CAVs that operate on a specific spatial scope that may be a road network …

How micro lecture videos trigger the motivation of learners of Coursera: A comparative study based on ARCS mode

H Deng, Y Shao, Y Tang, Z Qin - … International Conference of …, 2014 - ieeexplore.ieee.org
The relatively low retention rates of learners have an implication that learners might
disengage in a MOOC course. Engagement and motivation always go hand in hand. The …

Fuzzy integration of support vector regression models for anticipatory control of complex energy systems

M Alamaniotis, V Agarwal - International Journal of Monitoring and …, 2014 - igi-global.com
Anticipatory control systems are a class of systems whose decisions are based on
predictions for the future state of the system under monitoring. Anticipation denotes …

Very-short term forecasting of electricity price signals using a Pareto composition of kernel machines in smart power systems

M Alamaniotis, N Bourbakis… - 2015 IEEE Global …, 2015 - ieeexplore.ieee.org
In smart power distribution systems price forecasting is an indispensable participant tool for
developing purchase strategies. This paper places itself in price directed power systems …

Application of fuzzy multiplexing of learning Gaussian processes for the interval forecasting of wind speed

M Alamaniotis, G Karagiannis - IET Renewable Power …, 2020 - Wiley Online Library
Robust forecasting of wind speed values is a key element to effectively accommodate
renewable generation from wind in smart power systems. However, the stochastic nature of …

Multi-kernel anticipatory approach to intelligent control with application to load management of electrical appliances

M Alamaniotis, LH Tsoukalas - 2016 24th Mediterranean …, 2016 - ieeexplore.ieee.org
Anticipatory systems are systems whose change of state depends on present and future
information about the system itself as well as its environment. Making control decisions …

Dynamic data driven partitioning of smart grid using learning methods

A Nasiakou, M Alamaniotis, LH Tsoukalas… - Handbook of Dynamic …, 2018 - Springer
A plethora of energy management opportunities has emerged for electricity consumers and
producers by way of the transition from the current grid infrastructure to a smart grid. The aim …

Predictive based monitoring of nuclear plant component degradation using support vector regression

V Agarwal, M Alamaniotis, LH Tsoukalas - 2015 - osti.gov
Nuclear power plants (NPPs) are large installations comprised of many active and passive
assets. Degradation monitoring of all these assets is expensive (labor cost) and highly …

Dynamic Data Driven Partitioning of Smart Grid for Improving Power Efficiency by Combinining K-Means and Fuzzy Methods

A Nasiakou, M Alamaniotis, LH Tsoukalas… - Handbook of Dynamic …, 2022 - Springer
A plethora of energy management opportunities has emerged for electricity consumers and
producers by way of the transition from the current grid infrastructure to a smart grid. The aim …

Evaluation of human machine interface (HMI) in nuclear power plants with fuzzy logic method

PL Lagari, A Nasiakou, R Fainti, K Mao… - … & Applications (IISA), 2016 - ieeexplore.ieee.org
Dealing with issues related to safety of Nuclear Power Plants (NPPs) is of high importance
and priority for assuring nonstop energy production. To enhance safety, modernization and …