Hybrid gas turbine-solid oxide fuel cell power generation has the potential to create a positive economic and environmental impact. Annually, the U.S. spends over $235 billion on electricity, and electric utilities emit 550 million metric tons of carbon. The integration of distributed hybrid generation can reduce these emissions and costs through increased efficiencies. In this paper, a model i...

The research described in this paper addresses issues of designing a computationally effective decision support system which can assist a decision maker in making an optimal choice between several discrete alternatives. A new hybrid approach to multi-attribute decision making under uncertainty incorporating Neural Networks and the Dempster-Shafer theory of evidence is introduced. A neural netwo...

Weaver is a hybrid planning algorithm that can create plans in domains that include uncertainty, modelled either as incomplete knowledge of the initial state of the world, of the effects of plan steps or of the possible external events. The plans are guaranteed to exceed some given threshold probability of success. Weaver creates a Bayesian network representation of a plan to evaluate it, in wh...

Hybrid Life Cycle Assessment (HLCA) methods attempt to address the limitations regarding process coverage and resolution of more traditional Process- Input-Output Assessments (PLCA, IOLCA). Due use different units, HLCA rely on commodity price information convert physical units used in inventories monetary commonly models. However, prices for same can vary significantly between supply chains, o...

Passive systems are preferred tools for seismic control of buildings challenged by probabilistic nature of the input excitation. However, other types of uncertainty still exist in parameters of the control device even when optimally tuned. The present work concerns optimal design of multiple-tuned-mass-damper embedded on a shear building by a number of meta-heuristics. They include well-known g...

Nowadays computational intelligence methods are widely spread in different tasks solving in Data Mining under uncertainty, nonlinearity, and disturbed by different type of stochastic, chaotic noises conditions. In the paper the hybrid neuro-neo-fuzzy system of computational intelligence is proposed. This system is distinguished by the computational simplicity, the learning process high speed an...

Quantitative Feedback Theory (QFT) is employed to achieve time domain specifications on the tip position of a hybrid actuated single-link flexible manipulator. The manipulator payload conditions are varied to assess the robustness of the synthesised control system to parametric uncertainty. A combination of QFT multi input multi output (MIMO) design methods 1 (nonsequential) and 2 (sequential) ...

This paper presents a novel approach to building an integrated uncertainty quantification (UQ) methodology suitable for modern-day component-based approach for multi-physics simulation development. Our “hybrid” UQ methodology supports independent development of the most suitable UQ method, intrusive or non-intrusive, for each physics module by providing an algorithmic framework to couple these ...