Titlebook: Parallel and Distributed Computing, Applications and Technologies; 21st International C Yong Zhang,Yicheng Xu,Hui Tian Conference proceedin

Blandishment

书目名称Parallel and Distributed Computing, Applications and Technologies影响因子(影响力)




书目名称Parallel and Distributed Computing, Applications and Technologies影响因子(影响力)学科排名




书目名称Parallel and Distributed Computing, Applications and Technologies网络公开度




书目名称Parallel and Distributed Computing, Applications and Technologies网络公开度学科排名




书目名称Parallel and Distributed Computing, Applications and Technologies被引频次




书目名称Parallel and Distributed Computing, Applications and Technologies被引频次学科排名




书目名称Parallel and Distributed Computing, Applications and Technologies年度引用




书目名称Parallel and Distributed Computing, Applications and Technologies年度引用学科排名




书目名称Parallel and Distributed Computing, Applications and Technologies读者反馈




书目名称Parallel and Distributed Computing, Applications and Technologies读者反馈学科排名

Goblet-Cells

Short-Term Load Forecasting Based on CNN-BiLSTM with Bayesian Optimization and Attention Mechanism,ce, the data set is divided into four subsets with respect to four seasons. The performance of the proposed model is compared with other forecasting models by MAE, RMSE, MAPE, and . score. The experiment results show that the proposed model fits the actual values best and has the best forecasting performance among the contrast models.

hidebound

Preventing DDoS Attacks on Bitcoin Memory Pool by the Dynamic Fee Threshold Mechanism,sactions in Bitcoin from the malicious spam transactions. We also make an analysis and experiments on the method, to demonstrate its effectiveness and accuracy of detecting the malicious transactions.

Encephalitis

VEST

Kaizhi Chen,Wencheng Wei,Shangping Zhong,Longkun Guo

侵略

Fumin Qi,Xiao-Yuan Jing,Xiaoke Zhu,Xiaodong Jia,Li Cheng,Yichuan Dong,Ziseng Fang,Fei Ma,Shengzhong Feng

Evolve

AMITY

jarring

On the Non-ergodic Convergence Rate of the Directed Nonsmooth Composite Optimization,ve functions and .(1/.) for strongly convex objective functions, showing improvement relative to the rates . and . provided by the existing methods. Simulation examples further illustrate the effectiveness of the proposed method.

FAWN

Blood Leukocyte Object Detection According to Model Parameter-Transfer and Deformable Convolution,ental results show that compare our method with the traditional Faster RCNN object detection algorithm, . is 0.056 higher, . is 0.119 higher, with higher recall by 4%, and better accuracy by 5%. Thus, the method proposed in this paper can achieve highly accurate leukocyte detection.