4 resultados para License system

em Deakin Research Online - Australia


Relevância:

30.00% 30.00%

Publicador:

Resumo:

Lubricant technology must keep pace with the ever increasing demands to reduce energy use and increase service intervals. Ionic liquids were evaluated as lubricants for aluminium in the neat state and as additives in base oils. The ionic liquids formed protective layers that reduced friction and wear

Relevância:

30.00% 30.00%

Publicador:

Resumo:

 Utilizing MRI, this thesis identified wide-spread brain abnormalities in autism. White matter deficits were more pronounced in the left hemisphere, attributable to atypical myelination. Regarding the mirror neuron system, functional anomalies were situated in the right, dorsal, premotor cortex which further demonstrated reduced functional connectivity with the inferior parietal lobule.

Relevância:

30.00% 30.00%

Publicador:

Relevância:

30.00% 30.00%

Publicador:

Resumo:

This is an open access article under the CC BY-NC-ND license.Neuro-Fuzzy Systems (NFS) are computational intelligence tools that have recently been employed in hydrological modeling. In many of the common NFS the learning algorithms used are based on batch learning where all the parameters of the fuzzy system are optimized off-line. Although these models have frequently been used, there is a criticism on such learning process as the number of rules are needed to be predefined by the user. This will reduce the flexibility of the NFS architecture while dealing with different data with different level of complexity. On the other hand, online or local learning evolves through local adjustments in the model as new data is introduced in sequence. In this study, dynamic evolving neural fuzzy inference system (DENFIS) is used in which an evolving, online clustering algorithm called the Evolving Clustering Method (ECM) is implemented. ECM is an online, maximum distance-based clustering method which is able to estimate the number of clusters in a data set and find their current centers in the input space through its fast, one-pass algorithm. The 10-minutes rainfall-runoff time series from a small (23.22 km2) tropical catchment named Sungai Kayu Ara in Selangor, Malaysia, was used in this study. Out of the 40 major events, 12 were used for training and 28 for testing. Results obtained by DENFIS were then compared with the ones obtained by physically-based rainfall-runoff model HEC-HMS and a regression model ARX. It was concluded that DENFIS results were comparable to HEC-HMS and superior to ARX model. This indicates a strong potential for DENFIS to be used in rainfall-runoff modeling.