Titlebook: Emerging Research in Intelligent Systems; Proceedings of the C Miguel Botto-Tobar,Henry Cruz,Benjamin Durakovic Conference proceedings 2022

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書目名稱Emerging Research in Intelligent Systems影響因子(影響力)




書目名稱Emerging Research in Intelligent Systems影響因子(影響力)學(xué)科排名




書目名稱Emerging Research in Intelligent Systems網(wǎng)絡(luò)公開度




書目名稱Emerging Research in Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Emerging Research in Intelligent Systems被引頻次




書目名稱Emerging Research in Intelligent Systems被引頻次學(xué)科排名




書目名稱Emerging Research in Intelligent Systems年度引用




書目名稱Emerging Research in Intelligent Systems年度引用學(xué)科排名




書目名稱Emerging Research in Intelligent Systems讀者反饋




書目名稱Emerging Research in Intelligent Systems讀者反饋學(xué)科排名

Nutrient

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改變

Statistics and Neural Networks,he dynamic response of the building during a seism. Results show that the acceleration values increase as a function of the building height. Regarding the seismic event analyzed, the RMS values of acceleration identified on the basement were 0.26, 0.22, and 0.22?cm/s. and in the case of the eighth f

大罵

Neural Network Adjustment Algorithmsapplying Blockchain in IoT. Therefore, there is a need to evaluate the performance of Blockchain in different environments and new investigations that provide better results as computer vulnerabilities and their possible effects on devices used in IoT increase.

ANNUL

Neural Networks and Fuzzy Systems and those developed after participating in permanent training courses. The data was corroboree by obtaining a p-value of 0.007. Lifelong learning acquires a leading role when digital literacy and digital skills development are necessary for an emerging situation.

ANNUL

Neural Networks and Statistical Learning to the defined variables. In addition, a method was developed using an unsupervised machine learning algorithm in Python. The tools used for the development of this research were PRTG, Python, Pycaret Library, Collaboratory, Power BI for monitoring, development, and simulation respectively. For the

fertilizer

https://doi.org/10.1007/978-1-4471-3244-8t. Tests were carried out on the system by calculating the precision with different interfaces, and it was obtained that the one with the lowest margin of error is the interface where images and keywords are applied, this being the one used in the construction of the proposed system.

縱火

Yeshwant K. Muthusamy,Ronald A. Coleal and non-traditional methods. In that sense, Artificial Intelligence (AI) methods are crucial in the studies of CT image segmentation due to those methods automated all of the processes. The majority contributions of AI are the novel methods from its subfields of Deep Learning and Neural Networks.

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