Parameter optimisation is a significant but time consuming process that is inherent to conceptual hydrological models representing rainfall-runoff process. This study presents two modifications to achieve optimised results for a Tank Model in less computational time. Firstly, a modified Genetic algorithm (GA) is developed to enhance the fitness of the population consisting of possible solutions...

This paper provides a simulation-based approach to optimal portfolio selection. We take a Bayesian approach as it naturally accounts for estimation risk, i.e., parameter uncertainty, learning of state variables and models, and can incorporate prior beliefs about future return distributions. We specifically highlight two implementations with great potential in portfolio selection. First, for com...