Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ramkumar, Bharathi V.; Savitha, Sivasubramanian; Dhandapani, Anbarasu; Bhonsle, Mansi; Pokkuluri, Kiran Sree; Kirubanand, V.B. Title A name given to the resource Adaptive Fuzzy Heuristic Algorithm for Dynamic Data Mining in IoT Integrated Big Data Environments Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Journal of Fuzzy Extension and Applications;Volume;6;Issue;3;pp.615-636 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.22105/jfea.2024.484955.1676" target="_blank" rel="noreferrer noopener">https://doi.org/10.22105/jfea.2024.484955.1676</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008303515?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008303515?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Ramkumar B.V., Department of Computer Science (PG), Kristu Jayanti College, Karnataka, Bengaluru, 560077, India; Savitha S., Department of Information Science and Engineering, BMS Institute of Technology and Management, Karnataka, Bengaluru, 560064, India; Dhandapani A., Department of Electronics and Communication Engineering, Jaya Engineering College, Thiruninravur, Chennai, 602024, India; Bhonsle M., Department of Computer Science and Engineering, MIT Art, Design and Technology University, Pune, 412201, India; Pokkuluri K.S., Department of Computer Science and Engineering, Shri Vishnu Engineering College for Women, Bhimavaram, India; Kirubanand V.B., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India Description An account of the resource The explosion of Internet of Things (IoT) devices has created enormous amounts of real-time data, requiring sophisticated Data Mining Methods (DMT) that can rapidly extract valuable insights. Managing the computational complexity of processing high data volumes, integrating various IoT data formats, and ensuring that the system can scale are among the most significant issues. Fuzzy Dynamic Adaptive Classifier Optimization Analysis (FDACOA) is a method that has been suggested as an approach to the difficulties caused by changes in data patterns, processing in real-time, and data heterogeneity. By incorporating Adaptive Fuzzy Logic (AFL) and heuristic optimization, FDACOA enhances data classification accuracy and efficiency while simultaneously assuring that the algorithm can adapt to changes in data streams. This adaptability is crucial in IoT applications, where data fluctuation might affect analysis quality. FDACOA uses dynamic adaptation to alter classifier parameters based on real-time feedback to improve prediction accuracy and reduce computing costs. An optimization layer fine-tunes fuzzy rules and membership functions to optimize performance across data situations. Simulation analyses proved the algorithm's capacity to classify with high accuracy and low computational cost. Smart healthcare, predictive maintenance in industrial IoT, and intelligent transportation systems use FDACOA for real-time decision-making and data-driven insights. FDACOA is a viable approach for dynamic data mining in IoT-enabled big data contexts because of its faster, more accurate, and more adaptable simulation results. 2025, Research Expansion Alliance (REA). All rights reserved. Subject The topic of the resource Classification optimsization; Dynamic data mining; Fuzzy heuristic algorithm; Integrated big data environment; Internet of things Publisher An entity responsible for making the resource available Research Expansion Alliance (REA) Relation A related resource ISSN: 27831442; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online