Titlebook: Artificial Intelligence and Environmental Sustainability; Challenges and Solut Hui Lin Ong,Ruey-an Doong,Atulya K. Nagar Book 2022 The Edit

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书目名称Artificial Intelligence and Environmental Sustainability影响因子(影响力)




书目名称Artificial Intelligence and Environmental Sustainability影响因子(影响力)学科排名




书目名称Artificial Intelligence and Environmental Sustainability网络公开度




书目名称Artificial Intelligence and Environmental Sustainability网络公开度学科排名




书目名称Artificial Intelligence and Environmental Sustainability被引频次




书目名称Artificial Intelligence and Environmental Sustainability被引频次学科排名




书目名称Artificial Intelligence and Environmental Sustainability年度引用




书目名称Artificial Intelligence and Environmental Sustainability年度引用学科排名




书目名称Artificial Intelligence and Environmental Sustainability读者反馈




书目名称Artificial Intelligence and Environmental Sustainability读者反馈学科排名

和平主义者

Oluwayemi-Oniya Aderibigbe,Trynos Gumbo quality in near real time aiding faster decision-making and resulting in mitigation actions. The exponential digital transformations in every sector have led to platform technologies and in this chapter, we explore the network approaches platform ecosystems to adopt as opposed to a linear approach

Coronary

Lecture Notes in Networks and Systemsons. However, not all AI-based techniques are capable of real-time modelling. Therefore, this study is focussed on reviewing the AI-based techniques for real-time R-R modelling and discussing their capabilities, limitations, and potential areas for improvement. Finally, the potential future research

牙齿

Lecture Notes in Networks and Systems pharmaceutical tablets as functions of product formulation. The resulting rule-based model provides useful insights on how levels of additives can be optimized to give a product that performs well in the tableting process.

pulse-pressure

使腐烂

https://doi.org/10.1007/978-981-97-3991-2untry-level economies. The proposed hybrid approach is capable of mapping an initial causal network using DEMATEL and then training the network through FCM. The network attained an accuracy of 73.20% on training and 73.81% on testing, revealing economic attractiveness and consumer demand as signific

duplicate

Lecture Notes in Networks and Systems first period (past 1999–2003) and 83.07% for the second period (2014–2017), respectively. Maps further highlighted changes in LULC classes over time. The LULC classes had changed substantially due to natural processes and anthropogenic actions. The study demonstrated the potential use of remap to m

hemophilia

diathermy

Artificial Intelligence and Environmental SustainabilityChallenges and Solut

闪光东本

AI and Environmental Health: A Platform Ecosystem Perspective, quality in near real time aiding faster decision-making and resulting in mitigation actions. The exponential digital transformations in every sector have led to platform technologies and in this chapter, we explore the network approaches platform ecosystems to adopt as opposed to a linear approach