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

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書目名稱Neural Information Processing影響因子(影響力)




書目名稱Neural Information Processing影響因子(影響力)學(xué)科排名




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度




書目名稱Neural Information Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Neural Information Processing被引頻次




書目名稱Neural Information Processing被引頻次學(xué)科排名




書目名稱Neural Information Processing年度引用




書目名稱Neural Information Processing年度引用學(xué)科排名




書目名稱Neural Information Processing讀者反饋




書目名稱Neural Information Processing讀者反饋學(xué)科排名

松軟

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.

高深莫測(cè)

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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