Search Results - (( intelligence based asms algorithm ) OR ( intelligence based mach algorithm ))*

Exploring fruit fly evolutionary algorithm in a university examination timetabling environment by Abdul Rahman, Syariza, Benjamin, Aida Mauziah, Ramli, Razamin, Ku-Mahamud, Ku Ruhana, Omar, Mohd Faizal

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Face recognition-based real-time system for surveillance by Mahdi, F.P., Habib, M.M., Ahad, M.A.R., McKeever, S., Moslehuddin, A.S.M., Vasant, P.

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Evolutionary Integrated Heuristic with Gudermannian Neural Networks for Second Kind of Lane–Emden Nonlinear Singular Models by Kashif, Nisar, Zulqurnain, Sabir, Muhammad Asif Zahoor, Raja, Ag. Asri Ag., Ibrahim, Joel J. P. C., Rodrigues, Adnan, Shahid Khan, Manoj, Gupta, Aldawoud, Kamal, Danda B., Rawat

“…In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). …”
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Evolutionary integrated heuristic with gudermannian neural networks for second kind of lane– emden nonlinear singular models by Kashif Nisar, Zulqurnain Sabir, Muhammad Asif Zahoor Raja, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Adnan Shahid Khan, Manoj Gupta, Aldawoud Kamal, Danda B. Rawat

“…In this work, a new heuristic computing design is presented with an artificial intelligence approach to exploit the models with feed-forward (FF) Gudermannian neural networks (GNN) accomplished with global search capability of genetic algorithms (GA) combined with local convergence aptitude of active-set method (ASM), i.e., FF-GNN-GAASM to solve the second kind of Lane–Emden nonlinear singular models (LE-NSM). …”
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WiFi-based human activity recognition through wall using deep learning by Wong, Yan Chiew, Ahmed Abuhoureyah, Fahd Saad, Mohd Isira, Ahmad Sadhiqin

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