1. Shajahan, B. and S. Alavandar, 2018. Congestion controller for best effort networks using fuzzy inference system. J. Comput. Theor. Nanosci., 15: 40-46.
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2. Priya, N.S., R. Sasikala, S. Alavandar and L. Bharathi, 2018. Security aware trusted cluster based routing protocol for wireless body sensor networks. Wireless Pers. Commun., 102: 3393-3411.
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3. Lakshmanan, B., S. Ramasamy and S. Alavandar, 2016. Adaptive burst assembly algorithm for reducing burst loss and delay in OBS networks. Asian J. Inf. Technol., 15: 2123-2132.
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4. Kumar, S. and A. Srinivasan, 2016. Control of robot manipulator error using fpdi–iqga in neural network. J. Comput. Theor. Nanosci., 13: 1740-1748.
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5. Kumar, A.T. and A. Srinivasan, 2016. GRNN based inertia parameters identification of robot dynamics. Adv. Nat. Appl. Sci., 16: 115-119.
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6. Patil, S.G., S. Mandal, A.V. Hegde and S. Alavandar, 2011. Neuro-Fuzzy Based Approach for Wave Transmission Prediction of Horizontally Interlaced Multilayer Moored Floating Pipe Breakwater. Ocean Eng., 38: 186-196.
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7. Jain, T., S. Alavandar, S.V. Radhamohan and M.J. Nigam, 2010. Genetically-Bacterial Swarm Optimization: Fuzzy Pre-Compensated Pd Control Of Two-Link Rigid-Flexible Manipulator. Int. J. Intell. Comput. Cybern., 3: 463-494.
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8. Jain, T., M.J. Nigam and S. Alavandar, 2010. A Hybrid Genetically-Bacterial Foraging Algorithm Converged by Particle Swarm Optimisation for Global Optimisation. Int. J. Bio-Inspired Comput., 2: 340-348.
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9. Alavandar, S., T. Jain and M.J. Nigam, 2010. Hybrid bacterial foraging and particle swarm optimisation for fuzzy precompensated control of flexible manipulator. Int. J. Automation Control, 40: 234-251.
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10. Alavandar, S., T. Jain and M.J. Nigam, 2009. Particle swarm optimized hybrid fuzzy precompensated trajectory control of rigid-flexible manipulator. Int. J. Knowledge-Based Intell. Eng. Syst., 13: 155-167.
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11. Alavandar, S., T. Jain and M.J. Nigam, 2009. Bacterial foraging optimized hybrid fuzzy precompensated pd control of two link rigid - flexible manipulator. Int. J. Comput. Intell. Syst., 2: 51-59.
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12. Alavandar, S. and M.J. Nigam, 2009. New hybrid adaptive neuro fuzzy algorithms for manipulator control with uncertainties -comparative study. ISA Transactions, 48: 497-502.
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13. Alavandar, S. and M.J. Nigam, 2009. Comparative analysis of conventional and soft computing based control strategies for robot manipulators with uncertainties. Int. J. Comput. Cognition,. 7: 52-61.
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14. Alavandar, S. and M.J. Nigam, 2008. Neuro-Fuzzy based approach for inverse kinematics solution of industrial robot manipulators. Int. J. Comput. Commun. Control, 3: 224-234.
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15. Alavandar, S. and M.J. Nigam, 2008. Fuzzy PD+I control of a six dof robot manipulator. Ind. Robot Int. J., 35: 125-132.
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16. Alavandar, S. and M.J. Nigam, 2008. Adaptive neuro-fuzzy inference system based control of six dof robot manipulator. J. Eng. Sci. Technol. Rev., 1: 106-111.
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17. Alavandar, S., K.A.V. Sundaram and M.J. Nigam, 2007. Genetic algorithm based robot massage. J. Theor. Applied Inform. Technol., 3: 102-109.
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18. Alavandar, S. and M.J. Nigam, 2007. Tracking control of 3-DOF robot manipulator using genetic algorithm tuned fuzzy PID controller. J. Theor. Applied Inform. Technol., 3: 15-24.