Solving the task of local optima traps in data mining applications through intelligent mult-agent swarm and orthopair fuzzy sets (Record no. 22745)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250429102417.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250429b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 26033 |
| Author | Reddi, Kiran Kumar |
| 245 ## - TITLE STATEMENT | |
| Title | Solving the task of local optima traps in data mining applications through intelligent mult-agent swarm and orthopair fuzzy sets |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.14(3), Jan |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | ICT Academy |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 3263-3269p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Local optima traps pose a significant challenge in optimizing complex<br/>problems, particularly in data mining applications, where traditional<br/>algorithms may get stuck in suboptimal solutions. This study addresses<br/>this issue by combining the power of intelligent multi-agent swarm<br/>algorithms and orthopair fuzzy sets to enhance optimization processes.<br/>We propose a novel approach that leverages the collective intelligence<br/>of a multi-agent swarm system, enabling effective exploration and<br/>exploitation of solution spaces. Additionally, orthopair fuzzy sets are<br/>introduced to model and represent uncertainties inherent in data<br/>mining tasks, providing a more robust optimization framework. Our<br/>work contributes to the advancement of optimization techniques in data<br/>mining by offering a synergistic solution to local optima traps. The<br/>integration of intelligent multi-agent swarms and orthopair fuzzy sets<br/>enhances the algorithm’s adaptability and resilience, leading to<br/>improved convergence and better solutions. Experimental results<br/>demonstrate the efficacy of our proposed approach in overcoming local<br/>optima traps, showcasing superior performance compared to<br/>traditional algorithms. The hybrid system exhibits increased<br/>convergence rates and consistently discovers more accurate and diverse<br/>solutions across various data mining scenarios. |
| 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) | 26034 |
| Co-Author | Chengamma, P. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Chennai ICT Academy |
| Title | ICTACT Journal on Soft Computing (IJSC) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://ictactjournals.in/paper/IJSC_Vol_14_Iss_3_Paper_5_3263_3268.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 | 29/04/2025 | 2025-0724 | 29/04/2025 | 29/04/2025 | Articles Abstract Database |