104 resultados para Fuzzy sphere
Resumo:
In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.
Resumo:
Objectives: The Secondary Prevention of Heart disEase in geneRal practicE (SPHERE) trial has recently reported. This study examines the cost-effectiveness of the SPHERE intervention in both healthcare systems on the island of Ireland. Methods: Incremental cost-effectiveness analysis. A probabilistic model was developed to combine within-trial and beyond-trial impacts of treatment to estimate the lifetime costs and benefits of two secondary prevention strategies: Intervention - tailored practice and patient care plans; and Control - standardized usual care. Results: The intervention strategy resulted in mean cost savings per patient of 512.77 (95 percent confidence interval [CI], 1086.46-91.98) and an increase in mean quality-adjusted life-years (QALYs) per patient of 0.0051 (95 percent CI, 0.0101-0.0200), when compared with the control strategy. The probability of the intervention being cost-effective was 94 percent if decision makers are willing to pay €45,000 per additional QALY. Conclusions: Decision makers in both settings must determine whether the level of evidence presented is sufficient to justify the adoption of the SPHERE intervention in clinical practice. Copyright © Cambridge University Press 2010.
