"Energy Efficient Cloud Computing Using Artificial Neural Networks" - Information and Links:

Energy Efficient Cloud Computing Using Artificial Neural Networks - Info and Reading Options

"Energy Efficient Cloud Computing Using Artificial Neural Networks" and the language of the book is English.


“Energy Efficient Cloud Computing Using Artificial Neural Networks” Metadata:

  • Title: ➤  Energy Efficient Cloud Computing Using Artificial Neural Networks
  • Author: ➤  
  • Language: English

“Energy Efficient Cloud Computing Using Artificial Neural Networks” Subjects and Themes:

Edition Identifiers:

  • Internet Archive ID: ➤  httpsjournals.researchparks.orgindex.phpijhcsarticleview5049

AI-generated Review of “Energy Efficient Cloud Computing Using Artificial Neural Networks”:


"Energy Efficient Cloud Computing Using Artificial Neural Networks" Description:

The Internet Archive:

<div class="item abstract" style="padding:30px;color:rgba(0,0,0,0.87);font-family:tahoma, geneva, sans-serif;font-size:14px;background-color:rgb(255,255,255);"><p style="line-height:25px;margin:20px 0px 0px;">This effort focuses on building an intelligent, energy-efficient cloud architecture to improve cloud computing infrastructures. The rate at which cloud data gets modernized has increased, leading to more reviews comparing the various modernization methodologies and models. Several wealthy nations, including Turkey, have upgraded to more complicated and energy-efficient cloud infrastructure. We designed a Python application that uses an AI framework to maximize cloud computing's usage of computing resources and clean, renewable energy. This plan outlines concepts for a future neural network-trained digital ecosystem (ANN). The ANN model details energy forecasting tasks within a constrained system. Prominent corporations use AI to design policies to secure their cloud infrastructures and digital assets. Cloud computing systems were modernized by acquiring, normalizing, and transforming their file formats. Most cloud-based infrastructures were updated successfully. This was expected, given digital implementations dominate these systems. We'll investigate the energy consumption of AWS, AZURE, GCP, and Digital Ocean. Since most files were still on paper in 2015, the number of upgrades was modest. By 2020, a large part of cloud computing systems will be converted to digital format, with 98.68% accuracy for all cloud computing systems when trained on 80% of the data and evaluated on 20% of the data. Smart energy-efficient cloud solutions are replacing traditional data centers year by year. Smart energy-efficient cloud systems help preserve cloud computing systems and understand how cloud platforms are modernized and perform in energy prediction.</p><div><br /></div></div>

Read “Energy Efficient Cloud Computing Using Artificial Neural Networks”:

Read “Energy Efficient Cloud Computing Using Artificial Neural Networks” by choosing from the options below.

Available Downloads for “Energy Efficient Cloud Computing Using Artificial Neural Networks”:

"Energy Efficient Cloud Computing Using Artificial Neural Networks" is available for download from The Internet Archive in "texts" format, the size of the file-s is: 11.35 Mbs, and the file-s went public at Mon Apr 22 2024.

Legal and Safety Notes

Copyright Disclaimer and Liability Limitation:

A. Automated Content Display
The creation of this page is fully automated. All data, including text, images, and links, is displayed exactly as received from its original source, without any modification, alteration, or verification. We do not claim ownership of, nor assume any responsibility for, the accuracy or legality of this content.

B. Liability Disclaimer for External Content
The files provided below are solely the responsibility of their respective originators. We disclaim any and all liability, whether direct or indirect, for the content, accuracy, legality, or any other aspect of these files. By using this website, you acknowledge that we have no control over, nor endorse, the content hosted by external sources.

C. Inquiries and Disputes
For any inquiries, concerns, or issues related to the content displayed, including potential copyright claims, please contact the original source or provider of the files directly. We are not responsible for resolving any content-related disputes or claims of intellectual property infringement.

D. No Copyright Ownership
We do not claim ownership of any intellectual property contained in the files or data displayed on this website. All copyrights, trademarks, and other intellectual property rights remain the sole property of their respective owners. If you believe that content displayed on this website infringes upon your intellectual property rights, please contact the original content provider directly.

E. Fair Use Notice
Some content displayed on this website may fall under the "fair use" provisions of copyright law for purposes such as commentary, criticism, news reporting, research, or educational purposes. If you believe any content violates fair use guidelines, please reach out directly to the original source of the content for resolution.

Virus Scanning for Your Peace of Mind:

The files provided below have already been scanned for viruses by their original source. However, if you’d like to double-check before downloading, you can easily scan them yourself using the following steps:

How to scan a direct download link for viruses:

  • 1- Copy the direct link to the file you want to download (don’t open it yet).
    • (a free online tool) and paste the direct link into the provided field to start the scan.
  • 2- Visit VirusTotal (a free online tool) and paste the direct link into the provided field to start the scan.
  • 3- VirusTotal will scan the file using multiple antivirus vendors to detect any potential threats.
  • 4- Once the scan confirms the file is safe, you can proceed to download it with confidence and enjoy your content.

Available Downloads

  • Source: Internet Archive
  • Internet Archive Link: Archive.org page
  • All Files are Available: Yes
  • Number of Files: 15
  • Number of Available Files: 15
  • Added Date: 2024-04-22 12:02:26
  • Scanner: Internet Archive HTML5 Uploader 1.7.0
  • PPI (Pixels Per Inch): 300
  • OCR: tesseract 5.3.0-6-g76ae
  • OCR Detected Language: en

Available Files:

1- Text PDF

  • File origin: original
  • File Format: Text PDF
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks.pdf
  • Direct Link: Click here

2- Item Tile

  • File origin: original
  • File Format: Item Tile
  • File Size: 0.00 Mbs
  • File Name: __ia_thumb.jpg
  • Direct Link: Click here

3- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: httpsjournals.researchparks.orgindex.phpijhcsarticleview5049_files.xml
  • Direct Link: Click here

4- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: httpsjournals.researchparks.orgindex.phpijhcsarticleview5049_meta.sqlite
  • Direct Link: Click here

5- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: httpsjournals.researchparks.orgindex.phpijhcsarticleview5049_meta.xml
  • Direct Link: Click here

6- chOCR

  • File origin: derivative
  • File Format: chOCR
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_chocr.html.gz
  • Direct Link: Click here

7- DjVuTXT

  • File origin: derivative
  • File Format: DjVuTXT
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_djvu.txt
  • Direct Link: Click here

8- Djvu XML

  • File origin: derivative
  • File Format: Djvu XML
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_djvu.xml
  • Direct Link: Click here

9- hOCR

  • File origin: derivative
  • File Format: hOCR
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_hocr.html
  • Direct Link: Click here

10- OCR Page Index

  • File origin: derivative
  • File Format: OCR Page Index
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_hocr_pageindex.json.gz
  • Direct Link: Click here

11- OCR Search Text

  • File origin: derivative
  • File Format: OCR Search Text
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_hocr_searchtext.txt.gz
  • Direct Link: Click here

12- Single Page Processed JP2 ZIP

  • File origin: derivative
  • File Format: Single Page Processed JP2 ZIP
  • File Size: 0.01 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_jp2.zip
  • Direct Link: Click here

13- Page Numbers JSON

  • File origin: derivative
  • File Format: Page Numbers JSON
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_page_numbers.json
  • Direct Link: Click here

14- Scandata

  • File origin: derivative
  • File Format: Scandata
  • File Size: 0.00 Mbs
  • File Name: 27-39 Energy Efficient Cloud Computing Using Artificial Neural Networks_scandata.xml
  • Direct Link: Click here

15- Archive BitTorrent

  • File origin: metadata
  • File Format: Archive BitTorrent
  • File Size: 0.00 Mbs
  • File Name: httpsjournals.researchparks.orgindex.phpijhcsarticleview5049_archive.torrent
  • Direct Link: Click here

Search for “Energy Efficient Cloud Computing Using Artificial Neural Networks” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “Energy Efficient Cloud Computing Using Artificial Neural Networks” in Libraries Near You:

Read or borrow “Energy Efficient Cloud Computing Using Artificial Neural Networks” from your local library.

Buy “Energy Efficient Cloud Computing Using Artificial Neural Networks” online:

Shop for “Energy Efficient Cloud Computing Using Artificial Neural Networks” on popular online marketplaces.