Search Results - intelligence big ((((rsa algorithm) OR (path algorithm))) OR (bat algorithm))

Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
Get full text
Get full text
Get full text

Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review by Danyaro, K.U., Hussain, H.H., Abdullahi, M., Liew, M.S., Shawn, L.E., Abubakar, M.Y.

“…This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. …”
Get full text
Get full text

Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review by Danyaro, K.U., Hussain, H.H., Abdullahi, M., Liew, M.S., Shawn, L.E., Abubakar, M.Y.

“…This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. …”
Get full text
Get full text

Enhancing going concern prediction with Anchor explainable AI and attention-weighted XGBoost by Putthiporn Thanathamathee, Siriporn Sawangarreerak, Dinna Nina Mohd Nizam

“…The developed Attention-Weighted XGBoost algorithm, targeting essential financial indicators, markedly surpasses traditional approaches in prediction by its 98% accuracy, as evidenced by improved precision and recall. …”
Get full text
Get full text
Get full text