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Aws - Crossref

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Last Updated: 10 November 2022

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AWS-DAIE: Incremental Ensemble Short-Term Electricity Load Forecasting Based on Sample Domain Adaptation

Hence, this paper introduces a novel incremental ensemble model based on sample domain adaptation for adapting concept drift in a timely and accurate manner, as well as addressing the issue of inadequate training of the model due to a lack of concept drift samples. According to the model's results, according to current electricity load results, AWS-DAIE's primary aim is to detect concept drift on current electricity load data and create a new base predictor based on cumulative weighted sampling and then dynamically adjust the ensemble model's weights according to current electricity load results. We present the experimental results of the AWS-DAIE algorithm on electricity load data from four individual households and compared to several other outstanding algorithms for the purposes of demonstrating the feasibility and effectiveness of the aforementioned AWS-DAIE algorithm's proposed AWS-DAIE algorithm on electricity load measurements.

Source link: https://doi.org/10.3390/su142114205


A comparative study in Cloudera, Azure and AWS

Distributed cloud services have aided in the development and integration of complex IT services with little manual labor, which is also possible with the support of open source groups. However, some businesses do not see cloud services as a trusted or secure option for their information, so cloud service providers are considering hybrid solutions as a trend. In this paper, we will explore how to establish a general comparison tool for cloud services and Hadoop distributions that may be used as a basis for future comparison studies. Distributed cloud services have opened the door to simple use and integration of extensive IT services without much manual effort, which is possible with the support of open source communities. However, some businesses do not believe cloud services as a trusted or secure solution for their data, so cloud service providers are considering hybrid solutions as a trend.

Source link: https://doi.org/10.36227/techrxiv.21428007


A comparative study in Cloudera, Azure and AWS

Cloudera and AWS, Azure as cloud distribution services would be chosen by the We will use Cloudera as Hadoop distribution and AWS, Azure as cloud distribution services. Distributed cloud services have opened the door to rapid deployment and integration of extensive IT services without much manual effort, which is also possible with the support of open source communities. However, some businesses do not see cloud services as a trusted or safe option for their personal information, so cloud service providers are considering hybrid solutions as a trend. Open source communities have enabled easy access and integration of extensive IT services without much manual effort, which is possible with the help of open source communities. However, some businesses do not see cloud services as a trusted or secure option for their personal information, so cloud service providers are considering hybrid solutions as a trend.

Source link: https://doi.org/10.36227/techrxiv.21428007.v1


Retaining Human Responsibility in the Development and Use of Autonomous Weapon Systems: On Accountability for Violations of International Humanitarian Law Involving AWS

This paper discusses how the two central frameworks framed IHL's responsibility for IHL offenses, specifically the laws governing state accountability and individual criminal responsibilityu2014apply to the adoption and use of AWS. The report's goal is to aid policymakers in understanding the conditions that are appropriate to hold states and individuals accountable for IHL abuses; identify issues that could lead to IHL offences involving AWS development and use that could be difficult to detect, analyze, and attribute; and identify legislative steps that may help keep IHL respect and hold actors legally accountable.

Source link: https://doi.org/10.55163/ahbc1664

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions