Titlebook: Neural Information Processing; 24th International C Derong Liu,Shengli Xie,El-Sayed M. El-Alfy Conference proceedings 2017 Springer Interna

悲伤我

书目名称Neural Information Processing影响因子(影响力)




书目名称Neural Information Processing影响因子(影响力)学科排名




书目名称Neural Information Processing网络公开度




书目名称Neural Information Processing网络公开度学科排名




书目名称Neural Information Processing被引频次




书目名称Neural Information Processing被引频次学科排名




书目名称Neural Information Processing年度引用




书目名称Neural Information Processing年度引用学科排名




书目名称Neural Information Processing读者反馈




书目名称Neural Information Processing读者反馈学科排名

松软

激怒某人

Modeling Server Workloads for Campus Email Traffic Using Recurrent Neural Networksestigate the use of a Recurrent Neural Network (RNN) as time series modeling to model the server workload, which is a first for such a problem. Our results show that the use of RNN modeling leads in most cases to high modeling accuracy for all four campus email traffic datasets.

高深莫测

Accelerated Matrix Factorisation Method for Fuzzy Clustering also propose an efficient method to solve the proximal mapping problem when implementing nmAPG. Finally, the experiment results on synthetic and real-world datasets show the performances and feasibility of our method.

Mitigate

Mining Mobile Phone Base Station Data Based on Clustering Algorithms with Application to Public Trafodeling results of (1). Experimental results show that our model based on DBSCAN and GMM can effectively mine the significance of historical data of mobile phone base station and can successfully be applied to real-world problems like public traffic route design.

drusen

A Hybrid Method of Sine Cosine Algorithm and Differential Evolution for Feature Selection which helps the SCA to skip the local point. The proposed method is compared with other three algorithms to select the subset of features used eight UCI datasets. The experiments results showed that the proposed method provided better results than other methods in terms of performance measures and statistical test.

Glutinous

荒唐

去掉

Incremental Matrix Reordering for Similarity-Based Dynamic Data Setspose an original algorithm for the incremental reordering of a similarity matrix adapted to dynamic data sets. The proposed method is compared with state-of-the-art algorithms for static data-sets and applied to a dynamic data-set in order to demonstrate its efficiency.

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