郊区
发表于 2025-3-21 18:02:38
书目名称Microservices in Big Data Analytics影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0633454<br><br> <br><br>书目名称Microservices in Big Data Analytics读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0633454<br><br> <br><br>
semiskilled
发表于 2025-3-21 21:45:38
Improved DYMO-Based ACO for MANET Using Distance and Density of Nodes,onvention is contrasted and alternate conventions of its classification on the premise of different execution parameters. Result analysis shows that proposed protocol performs superior to the different existing protocols like AODV, TORA, DYMO, M-DYMO, and ACO.
COLON
发表于 2025-3-22 00:39:02
Comparison of Execution Time of Mobile Application Using Equal Division and Profile-Based Algorithme implementation of execution of the compute-intensive mobile application on the local mobile device and mobile ad hoc cloud and compares the execution time. This paper also compares the application execution time with the application which is distributed equally and based on the profile of mobile d
自作多情
发表于 2025-3-22 06:52:00
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做方舟
发表于 2025-3-22 08:45:02
Prediction of Underwater Surface Target Through SONAR: A Case Study of Machine Learning,, and AUC came out to be 0.92. With random forest algorithm, the results are further optimized by feature selection to get the accuracy of 90%. Assuring results are found, when the fulfillment of the designed groundwork is set side by side with the standard classifiers like SVM, random forest, etc.,
Microgram
发表于 2025-3-22 15:34:16
Big Data Machine Learning Framework for Drug Toxicity Prediction,of 96.20%, the results are compared with standard machine learning models like random forest, AdaBoost, Naive Bayes, etc., and are found to be much better than these classifiers. With the increase in toxicity in environment, this framework will play a significant role in improving lifestyle.
使高兴
发表于 2025-3-22 20:35:45
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neutral-posture
发表于 2025-3-22 22:38:46
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意外
发表于 2025-3-23 02:29:34
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MAIM
发表于 2025-3-23 08:56:12
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