Titlebook: Computational Science – ICCS 2019; 19th International C Jo?o M. F. Rodrigues,Pedro J. S. Cardoso,Peter M.A Conference proceedings 2019 Spri

老鼠系領(lǐng)帶

書目名稱Computational Science – ICCS 2019影響因子(影響力)




書目名稱Computational Science – ICCS 2019影響因子(影響力)學(xué)科排名




書目名稱Computational Science – ICCS 2019網(wǎng)絡(luò)公開度




書目名稱Computational Science – ICCS 2019網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Science – ICCS 2019被引頻次




書目名稱Computational Science – ICCS 2019被引頻次學(xué)科排名




書目名稱Computational Science – ICCS 2019年度引用




書目名稱Computational Science – ICCS 2019年度引用學(xué)科排名




書目名稱Computational Science – ICCS 2019讀者反饋




書目名稱Computational Science – ICCS 2019讀者反饋學(xué)科排名

疲勞

正常

Carcinogenesis

Aggrandize

Efficient Parallel Associative Classification Based on Rules Memoizations introduced to reorder computations by affinity, improving frequent-demanded association rules memoization in typical cache strategies. The experiments results show that our similarity-based metric maximizes the reuse of rules cached and, consequently, improve application performance, with gains up

驚呼

Anomaly Detection in Social Media Using Recurrent Neural Networknitial clustering step with the K-Nearest Neighbor (KNN) algorithm is proposed before training the result with a Recurrent Neural Network (RNN). The results of a preliminary application of the KNN phase before the RNN phase produces a quantitative and measureable improvement in the detection of outl

驚呼

BULLY

An Innovative and Reliable Water Leak Detection Service Supported by Data-Intensive Remote Sensing Pctive infrastructure repairs with the required degree of confidence on the detected leaks. The web platform allows for both data analysis and visualization of Sentinel images and relevant leak indicators at the sites selected by the user. The user can also provide aerial imagery inputs, to be proces

COKE

Kernel Embedded Nonlinear Observational Mappings in the Variational Mapping Particle Filteretween the state and observational spaces the so-called ensemble space and an RKHS approximation in which the observational mapping is embedded in an RKHS and the gradient is derived there. The approximations are evaluated for highly nonlinear observational operators and in a low-dimensional chaotic

Indolent