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In this paper, stochastic optimisation and risk estimation techniques are applied to the problem of hydroelectric generator design. Optimisation results from deterministic simulations can involve considerable risks due to unavoidable variations in system properties as well as environmental conditions. Therefore, stochastic simulation is used to include the effects of parameter scatter and noise effects in the computer models. This allows the evaluation of the scatter in performance and thus an assessment of reliability and quality of the simulated system.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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