Within the renewable energy canopy, solar energy has emerged as a potentially viable energy source to mitigate the increase in greenhouse gas emissions from fossil fuel combustion and address the ...

Data and code associated with paper "On the development of a practical Bayesian optimisation algorithm for expensive experiments and simulations with changing environmental conditions" currently in ...

This project applies Bayesian Optimization (BO) to optimize the structural features of a simulated drug candidate. The goal is to maximize bioavailability (measured by logP) while keeping the molecule ...

Abstract: This paper investigates a production decision optimisation model based on heuristic algorithms, using genetic algorithms, simulated annealing algorithms, Monte Carlo algorithms, etc., with ...

Abstract: We propose an adaptive optimisation approach for tuning stochastic model predictive control (MPC) hyper-parameters while jointly estimating probability distributions of the transition model ...

In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, ...