caa a22 4500 606159401 CHVBK 20210128100624.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s00521-015-1841-z doi (NATIONALLICENCE)springer-10.1007/s00521-015-1841-z Design and application of nature inspired computing approach for nonlinear stiff oscillatory problems [Elektronische Daten] [Junaid Khan, Muhammad Raja, Muhammed Syam, Shujaat Tanoli, Saeed Awan] In this paper, meta-heuristic intelligent approaches are developed for handling nonlinear oscillatory problems with stiff and non-stiff conditions. The mathematical modeling of these oscillators is accomplished using feed-forward artificial neural networks (ANNs) in the form of an unsupervised manner. The accuracy as well as efficiency of the model is subject to the tuning of adaptive parameters for ANNs that are highly stochastic in nature. These optimal weights are carried out with swarm intelligence and pattern search methods hybridized with an efficient local search technique based on constraints minimization known as active set algorithm. The proposed schemes are validated on various stiff and non-stiff variants of the oscillator. The significance, applicability and reliability of the proposed scheme are well established based on comparison made with the results of standard numerical solver. The Natural Computing Applications Forum, 2015 Van der Pol oscillators nationallicence Neural networks nationallicence Swarm intelligence nationallicence Active set algorithm nationallicence Pattern search nationallicence Khan Junaid Faculty of Engineering Science and Technology, Hamdard University, Islamabad Campus, Islamabad, Pakistan aut Raja Muhammad Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut Syam Muhammed Department of Mathematical Sciences, UAE University, Box 1551, Al-Ain, UAE aut Tanoli Shujaat Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut Awan Saeed Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut Neural Computing and Applications Springer London 26/7(2015-10-01), 1763-1780 0941-0643 26:7<1763 2015 26 521 https://doi.org/10.1007/s00521-015-1841-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1841-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Khan Junaid Faculty of Engineering Science and Technology, Hamdard University, Islamabad Campus, Islamabad, Pakistan aut NATIONALLICENCE 700 1- Raja Muhammad Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut NATIONALLICENCE 700 1- Syam Muhammed Department of Mathematical Sciences, UAE University, Box 1551, Al-Ain, UAE aut NATIONALLICENCE 700 1- Tanoli Shujaat Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut NATIONALLICENCE 700 1- Awan Saeed Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/7(2015-10-01), 1763-1780 0941-0643 26:7<1763 2015 26 521