Titlebook: Computational Intelligence and Intelligent Systems; 9th International Sy Kangshun Li,Wei Li,Yong Liu Conference proceedings 2018 Springer N

Grant

書目名稱Computational Intelligence and Intelligent Systems影響因子(影響力)




書目名稱Computational Intelligence and Intelligent Systems影響因子(影響力)學(xué)科排名




書目名稱Computational Intelligence and Intelligent Systems網(wǎng)絡(luò)公開度




書目名稱Computational Intelligence and Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Intelligence and Intelligent Systems被引頻次




書目名稱Computational Intelligence and Intelligent Systems被引頻次學(xué)科排名




書目名稱Computational Intelligence and Intelligent Systems年度引用




書目名稱Computational Intelligence and Intelligent Systems年度引用學(xué)科排名




書目名稱Computational Intelligence and Intelligent Systems讀者反饋




書目名稱Computational Intelligence and Intelligent Systems讀者反饋學(xué)科排名

大都市

腫塊

yohimbine

Bacterial Foraging Algorithm Based on Reinforcement Learning for Continuous Optimizationser (RBCFO) based on reinforcement learning (RL) and self-adaptive search strategy for continuous optimizations. The algorithm aims to enhance the individual search efficiency during the evolution process via exploiting the RL mechanism in the multi-operations decision level and the adaptive search s

助記

極力證明

Traffic Condition Assessment Based on Support Vectors Machine Using Intelligent Transportation SysteS information. There were study results as examples by means of the tool of inductive loop detectors, which were collected to be used as study materials, including 1-37, I-10 and 1-410 in San Antonio. It’s usual to use Support Vectors Machine that is one kind of new data dig technology to absorb dif

極力證明

Bidirectional Negative Correlation Learningcorrelation learning, the learning target on a give data point was set to be the same for all the individual learners in the committee. The same learning target could lead the individual learners to become similar to each other if the learning process would be conducted for long. In order to create

corporate

蜿蜒而流

A Multi-task Learning Approach for Mandarin-English Code-Switching Conversational Speech Recognitional speech recognition (MECS-CSR) (primary task) and language identification (LID) (auxiliary task). In our approach, the hidden layers of the DNNs for primary task fuse with ones of the DNN for auxiliary task by sharing weights/bias parameters. Extensive experiments are carried out on LDC2015S04 and

intuition

Feature Selection of Network Flow Based on Machine Learning features and categories, but information gain algorithm only considers the contribution values of individual feature to classification. It combines the subsequent learning algorithm to set appropriate threshold and complete feature selection, thus the consideration of redundancy between features ar