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Understanding quantum computing's most troubling problem—the barren plateau
Los Alamos National Laboratory has led the world in trying to understand one of the most frustrating barriers that faces ...
Understanding us: Researchers apply algorithm to decode complex genome sequences
Over the last 10 years, breakthroughs in understanding the genetic instructions passed from parent to offspring have put ...
Frontiers7mon
A comparative study of different deep learning methods for time-series probabilistic residential load power forecasting
Residential load power is decomposed into deterministic and stochastic components ... The optimal parameters of the GMM are obtained by the EM algorithm, resulting in the following probability density ...
Scientific Research Publishing1y
Sim-to-Real: A Performance Comparison of PPO, TD3, and SAC Reinforcement Learning Algorithms for Quadruped Walking Gait Generation ()
The performance of the state-of-the-art Deep Reinforcement algorithms such as Proximal Policy Optimization, Twin Delayed Deep Deterministic Policy Gradient, and Soft Actor-Critic for generating a ...
SciELO1y
A GRASP ALGORITHM FOR THE CONTAINER LOADING PROBLEM WITH MULTI-DROP CONSTRAINTS
This paper studies a variant of the container loading problem in which to the ... in the solution are then packed again using the deterministic constructive procedure. In this call of the ...
Frontiers2y
Developing an Artificial Hummingbird Algorithm for Probabilistic Energy Management of Microgrids Considering Demand Response
It achieves good results using the same procedures used with the deterministic ... well-known algorithms to demonstrate its robustness. Also, a probabilistic EM using hybrid AHA-PEM to consider the ...
IEEE5y
Reinforced Deterministic and Probabilistic Load Forecasting via
Abstract: Both deterministic and probabilistic load forecasting (DLF and PLF) are of critical importance to reliable and economical power system operations. However, most of the widely used ...