Abstract: We introduce an optimization assisted by a neural network (ONN) predictor to the electromagnetic community. ONN belongs to the class of the surrogate model-based optimization approaches, and ...

Given that extreme weather disturbances frequently threaten the safe and stable operation of new power systems, the uncertainty of source–load forecasting has become a particular bottleneck affecting ...

EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast. Evolutionary algorithms forms a family of ...

The stock markets contribute immensely to the growth of the economy. Stock price changes do not only show how companies are performing in financial terms, but they also determine the way people invest ...

Faculty of Engineering Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) ...

Abstract: This paper presents the hierarchical Q-learning path planning (HQPP) architecture for solving the cooperative tracking control problem of multi-agent systems (MASs) with lumped uncertainties ...

Crack formation is a common phenomenon in engineering structures, which can cause serious damage to the safety and health of these structures. An important method of ensuring the safety and health of ...

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.

The uncertainty of renewable energy and demand response brings many challenges to the microgrid energy management. Driven by the recent advances and applications of deep reinforcement learning a ...

Traditional neural networks struggle to manage long and complex data sequences effectively. Incorporating an attention layer can enhance a model's ability to focus on important information. If we are ...