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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書(shū)目名稱Artificial Intelligence and Environmental Sustainability影響因子(影響力)




書(shū)目名稱Artificial Intelligence and Environmental Sustainability影響因子(影響力)學(xué)科排名




書(shū)目名稱Artificial Intelligence and Environmental Sustainability網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Artificial Intelligence and Environmental Sustainability網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Artificial Intelligence and Environmental Sustainability被引頻次




書(shū)目名稱Artificial Intelligence and Environmental Sustainability被引頻次學(xué)科排名




書(shū)目名稱Artificial Intelligence and Environmental Sustainability年度引用




書(shū)目名稱Artificial Intelligence and Environmental Sustainability年度引用學(xué)科排名




書(shū)目名稱Artificial Intelligence and Environmental Sustainability讀者反饋




書(shū)目名稱Artificial Intelligence and Environmental Sustainability讀者反饋學(xué)科排名

和平主義者

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

牙齒

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

使腐爛

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

閃光東本

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