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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | Forecasting Revenue in Multi-Tiered Cloud Sales Models Using Hybrid Machine Learning Ensembles |
| Authors Name: | Manish Ravindra Sharath |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_208595
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| Published Paper Id: | IJRTI2512115 |
| Published In: | Volume 10 Issue 12, December-2025 |
| DOI: | https://doi.org/10.56975/ijrti.v10i12.208595 |
| Abstract: | The question of the prediction of the earnings in multi-level cloud selling models is also a crucial issue related to the mismatch between the services that are offered at the IaaS, PaaS, and SaaS levels and the utilization trends of the consumers. The traditional forecasting models cannot be used to work in such environments. The paper provides the summary of the present condition of the hybrid machine learning ensembles and their use in predicting the revenue of the cloud systems. It is actively participating in efforts to incorporate edge cloud systems, anomaly detection mechanisms, interpretable AI systems, and trusted data infrastructures into revenue forecasting frameworks. Ensemble methods involving statistical techniques, deep learning, and reinforcement learning will presumably furnish the revenue prediction engines with more accurate, transparent, and real-time revenue data. The issue of whether irrevocable protocols of data interchange exist and the rationale behind fostering a responsible and sensible predictive culture is also addressed. The results indicate that properly formulated hybrid artificial systems may present the scale and extensive-based resolutions that can be implemented to drive the desired plan of finances in the multi-layered clouds. |
| Keywords: | Cloud revenue forecasting, Hybrid machine learning, Edge-cloud architecture, Interpretable AI |
| Cite Article: | "Forecasting Revenue in Multi-Tiered Cloud Sales Models Using Hybrid Machine Learning Ensembles", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.b140-b145, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512115.pdf |
| Downloads: | 000170 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2512115
Registration ID:208595
Published In: Volume 10 Issue 12, December-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v10i12.208595
Page No: b140-b145 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2512115 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2512115 |
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ISSN: 2456-3315
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