Titlebook: Advances in Computational Collective Intelligence; 12th International C Marcin Hernes,Krystian Wojtkiewicz,Edward Szczerbi Conference proce

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書(shū)目名稱(chēng)Advances in Computational Collective Intelligence影響因子(影響力)




書(shū)目名稱(chēng)Advances in Computational Collective Intelligence影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Advances in Computational Collective Intelligence網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Advances in Computational Collective Intelligence網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Advances in Computational Collective Intelligence被引頻次




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書(shū)目名稱(chēng)Advances in Computational Collective Intelligence年度引用




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書(shū)目名稱(chēng)Advances in Computational Collective Intelligence讀者反饋




書(shū)目名稱(chēng)Advances in Computational Collective Intelligence讀者反饋學(xué)科排名

濃縮

Business and Sustainability: An Introductionor example, such circumstances appear typically in genetic data sets. In such cases, feature clustering can become a useful tool in classification or prognosis tasks. Feature clustering can be performed through the minimization of the convex and piecewise linear (.) criterion functions.

craven

https://doi.org/10.1007/978-3-030-63119-2artificial intelligence; computational linguistics; computer networks; computer systems; computer vision

折磨

978-3-030-63118-5Springer Nature Switzerland AG 2020

掙扎

Ptsd429

終止

Redefining Corporate Social Responsibility,erstand the causes and predict the severity level of a particular type of accident upfront, we can take necessary steps in the proper time to lessen the damages. In this study, we have built some predictive models of different homogeneous road crash groups of Bangladesh using machine learning method

軌道

https://doi.org/10.1007/978-3-319-07239-5ls are leveraged for predicting unconfined compression coefficient with respect to standard penetration test (N-value), depth and soil type. The study is focused on a particular correlation of undrained shear strength of clay (Cu) with the standard penetration strength. The data used is from 14 no.

Optimum

https://doi.org/10.1007/978-3-319-07239-5contamination, significantly increased recycling yield, and superior recovery material quality. This recycling model is problematic however, as it is prone to human error and community-level participation is difficult to incentivise with the greater inconvenience being placed on consumers. This pape

llibretto

https://doi.org/10.1007/978-3-319-07239-5ol And Data Acquisition) systems very often acquire many operational parameters that have no further analytical use. The variability of recorded signals very often depends on the machine load, as well as organizational and technical aspects. Therefore, SCADA systems can be a practically free source