This paper introduces a novel physical-inspired metaheuristic algorithm called “Light Spectrum Optimizer (LSO)” for continuous optimization problems. The inspiration the proposed is light dispersions with different angles while passing through rain droplets, causing meteorological phenomenon of colorful rainbow spectrum. In order to validate algorithm, three experiments are conducted. First, LS...

Efficient fault diagnosis of power transformer can effectively ensure the safe and stable operation system. Considering that effect traditional Random Forest (RF) is seriously affected by initial parameters, this paper proposes a RF algorithm based on Grey Wolf Optimization (GWO-RF) to improve accuracy identification. The uses GWO optimize total number decision trees depth maximum tree, balanci...

Landslide displacement prediction is essential to establish the early warning system (EWS). According dynamic characteristics of landslide evolution and shortcomings traditional static model, a model based on long short-term memory (LSTM) neural networks was proposed. Meanwhile, Variational mode decomposition (VMD) theory used decompose cumulative triggering factors, which not only give clear p...

When individuals interact with one another to accomplish specific goals, they learn from others’ experiences achieve the tasks at hand. The same holds for learning in virtual environments, such as video games. Deep multiagent reinforcement shows promising results terms of completing many challenging tasks. To demonstrate its viability, most algorithms use value decomposition multiple agents. gu...

Abstract With the rapid development of modern wireless technology, it is necessary to continuously optimize microwave devices meet higher requirements communication systems. In this paper, we propose a device optimization method based on extreme learning machine (ELM) and gray wolf optimizer (GWO). adopt GWO parameters ELM establish mapping relationships between design their responses. Accordin...

Abstract We focus on the performances of three nature-inspired metaheuristic methods for optimization time-domain electromagnetic (TDEM) data: Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) algorithms. While GA PSO have been used in a plethora geophysical applications, GWO has received little attention literature so far, despite promising outcomes. This ...

Since Grey Wolf Optimizer (GWO) first introduction, it continues to be used extensively today, owing its simplicity, easy handling, and applicability a wide range of problems. Although there are many different GWO variants in the literature, problem that produces early convergence inefficient results have still continued emerge their variants. In order overcome drawbacks theGWO, theGWO integrat...