Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Data has become a crucial element for contemporary enterprises; however, deriving practical insights from its immense volume remains an intricate obstacle. This paper examines the capabilities of three bio-inspired computational intelligence (CI) methods -Genetic Algorithms (GAs), Fuzzy Logic (FL), and Swarm Intelligence (SI) -in improving data analytics for business optimization and decision-making. The researcher thoroughly examines the fundamental principles of each technique, emphasizing their inherent advantages and appropriateness for addressing practical business challenges. By reviewing recent research and real-world examples, the researcher illustrates how Genetic Algorithms (GAs) can enhance the efficiency of resource allocation, Fuzzy Logic (FL) can effectively handle uncertainty in risk assessment, and Swarm Intelligence (SI) can streamline logistics and scheduling processes.
S.M.A.N.M Subasinghe. 2026. \u201cLeveraging Business-Inspired Computational Intelligence Techniques for Enhanced Data Analytics: Applications of Genetic Algorithms, Fuzzy Logic, and Swarm Intelligence\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 24 (GJCST Volume 24 Issue D1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 101
Country: Sri Lanka
Subject: Global Journal of Computer Science and Technology - D: Neural & AI
Authors: S.M.A.N.M Subasinghe (PhD/Dr. count: 0)
View Count (all-time): 238
Total Views (Real + Logic): 1164
Total Downloads (simulated): 29
Publish Date: 2026 01, Fri
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Neural Networks and Rules-based Systems used to Find Rational and
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Data has become a crucial element for contemporary enterprises; however, deriving practical insights from its immense volume remains an intricate obstacle. This paper examines the capabilities of three bio-inspired computational intelligence (CI) methods -Genetic Algorithms (GAs), Fuzzy Logic (FL), and Swarm Intelligence (SI) -in improving data analytics for business optimization and decision-making. The researcher thoroughly examines the fundamental principles of each technique, emphasizing their inherent advantages and appropriateness for addressing practical business challenges. By reviewing recent research and real-world examples, the researcher illustrates how Genetic Algorithms (GAs) can enhance the efficiency of resource allocation, Fuzzy Logic (FL) can effectively handle uncertainty in risk assessment, and Swarm Intelligence (SI) can streamline logistics and scheduling processes.
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