Titlebook: Business Intelligence; 7th International Co Mohamed Fakir,Mohamed Baslam,Rachid El Ayachi Conference proceedings 2022 Springer Nature Switz

阿諛奉承

書目名稱Business Intelligence影響因子(影響力)




書目名稱Business Intelligence影響因子(影響力)學科排名




書目名稱Business Intelligence網(wǎng)絡(luò)公開度




書目名稱Business Intelligence網(wǎng)絡(luò)公開度學科排名




書目名稱Business Intelligence被引頻次




書目名稱Business Intelligence被引頻次學科排名




書目名稱Business Intelligence年度引用




書目名稱Business Intelligence年度引用學科排名




書目名稱Business Intelligence讀者反饋




書目名稱Business Intelligence讀者反饋學科排名

Coterminous

Grasping

Decision Boundary to Improve the Sensitivity of Deep Neural Networks Modelsy decreases during standard training. However, adversarial training increases this distance, which improve the performance of our model. Our work presents a new solution to the deep neural networks sensitivity problem. We found a very strong relationship between the efficiency of the deep neural net

Metastasis

粗魯?shù)娜?/a>

Deep Reinforcement Learning for?Bitcoin Tradinghieve an optimal policy. The profit reward functions and Sharpe ratio are used to assess the proposed DRL. The results of the experiments demonstrate that combining three agents is the most efficient strategy for automatic bitcoin trading.

orthodox

Increasing Student Engagement in Lessons and Assessing MOOC Participants Through Artificial Intelligtudent‘s comprehension of the video‘s material. machine-generated questions performed comparably to human-generated questions when it came to judging skill and resemblance. Additionally, the findings indicate that the majority of the questions generated improve e-assessment when the new technology i

Assignment

CANDY

SLAG

arterioles

Alberto Del Bimbo,Pietro Pala,Enrico Vicariodoop framework to overcome the issue of long runtime of huge data sets. Also, a comparisons of the proposed model’s effectiveness with other existing models in the literature is carried out and the experimental results shown that our suggested parallel fuzzy model surpasses the baseline models by a