International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-12,Issue-9  ( Sep, 2024 )
Past issues
  1. Volume-12,Issue-8  ( Aug, 2024 )
  2. Volume-12,Issue-7  ( Jul, 2024 )
  3. Volume-12,Issue-6  ( Jun, 2024 )
  4. Volume-12,Issue-5  ( May, 2024 )
  5. Volume-12,Issue-4  ( Apr, 2024 )
  6. Volume-12,Issue-3  ( Mar, 2024 )
  7. Volume-12,Issue-2  ( Feb, 2024 )
  8. Volume-12,Issue-1  ( Jan, 2024 )
  9. Volume-11,Issue-12  ( Dec, 2023 )
  10. Volume-11,Issue-11  ( Nov, 2023 )

Statistics report
Feb. 2025
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 141
Paper Published : 1672
No. of Authors : 4423
  Journal Paper


Paper Title :
Data Analysis and Data Prediction Model

Author :Lakshit, Pooja Sharma, Meet Khurana

Article Citation :Lakshit ,Pooja Sharma ,Meet Khurana , (2024 ) " Data Analysis and Data Prediction Model " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 70-74, Volume-12,Issue-8

Abstract : This paper explores the design and implementation of an advanced data analysis and prediction model aimed at enhancing decision-making processes across various domains. The proposed model integrates machine learning algorithms with statistical analysis techniques to predict future trends accurately based on historical data. Key features include the use of neural networks for pattern recognition, regression analysis for trend forecasting, and clustering algorithms for identifying data groupings. To validate the model, a comprehensive series of experiments were conducted using real-world datasets from diverse sectors such as finance, healthcare, and retail. The performance metrics, including accuracy, precision, and recall, were benchmarked against traditional prediction models. Additionally, the model’s robustness was tested under different scenarios to assess its generalizability and reliability. Results demonstrated that the proposed prediction model significantly outperforms existing models in terms of prediction accuracy and computational efficiency. Furthermore, the integration of real-time data processing capabilities enables timely and actionable insights. Keywords - Machine Learning Algorithms, Neural Networks, Regression Analysis, Trend Forecasting

Type : Research paper

Published : Volume-12,Issue-8


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-21179   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 18
| Published on 2024-11-19
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY