Improvised method using neuro-fuzzy system for financial time series forecasting (Record no. 22721)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250425102950.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250425b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25996 |
| Author | Gandhi, Mohd. Asif |
| 245 ## - TITLE STATEMENT | |
| Title | Improvised method using neuro-fuzzy system for financial time series forecasting |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.14(4), Apr |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | ICT Academy |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 3328-3333p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Financial time series forecasting is crucial for making informed<br/>investment decisions. This study proposes an improvised method<br/>utilizing a Neuro-Fuzzy System (NFS) for enhanced forecasting<br/>accuracy. Traditional forecasting methods often struggle with the<br/>nonlinear and dynamic nature of financial time series data. NFS<br/>integrates neural network and fuzzy logic techniques, offering a robust<br/>framework for modeling complex relationships within financial data.<br/>The proposed method employs NFS to adaptively learn and model the<br/>intricate patterns present in financial time series data. It combines the<br/>strengths of neural networks in learning complex patterns and fuzzy<br/>logic in handling uncertainty and imprecision. This study contributes<br/>by introducing an innovative approach to financial time series<br/>forecasting, leveraging the capabilities of NFS to improve forecasting<br/>accuracy and reliability. Experimental results demonstrate the<br/>effectiveness of the proposed method in accurately forecasting<br/>financial time series data. The method outperforms traditional<br/>forecasting techniques, showcasing its potential for practical<br/>applications in financial markets. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25997 |
| Co-Author | Lekshmi Sri, S. M. |
| 773 0# - HOST ITEM ENTRY | |
| Title | ICTACT Journal on Soft Computing (IJSC) |
| Place, publisher, and date of publication | Chennai ICT Academy |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://ictactjournals.in/paper/IJSC_Vol_14_Iss_4_Paper_4_3328_3333.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 25/04/2025 | 2025-0670 | 25/04/2025 | 25/04/2025 | Articles Abstract Database |