Publications










    Journal Articles - International Refereed

  1. Wang, Y., Wang, H., Srinivasan, D., & Hu, Q. (2019). Robust functional regression for wind speed forecasting based on Sparse Bayesian learning. Renewable Energy, 132, 43-60. doi:10.1016/j.renene.2018.07.083

  2. Mehta, R., Verma, P., Srinivasan, D., & Yang, J. (2019). Double-layered intelligent energy management for optimal integration of plug-in electric vehicles into distribution systems. Applied Energy, 233-234, 146-155. doi:10.1016/j.apenergy.2018.10.008

  3. Zhang, W., Gandhi, O., Quan, H., Rodríguez-Gallegos, C. D., & Srinivasan, D. (2018). A multi-agent based integrated volt-var optimization engine for fast vehicle-to-grid reactive power dispatch and electric vehicle coordination. Applied Energy, 229, 96-110. doi:10.1016/j.apenergy.2018.07.092

  4. Zhang, W., Quan, H., & Srinivasan, D. (2018). Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination. Energy, 160, 810-819. doi:10.1016/j.energy.2018.07.019

  5. Kumar Nunna, H. S. V. S., Battula, S., Doolla, S., & Srinivasan, D. (2018). Energy Management in Smart Distribution Systems with Vehicle-To-Grid Integrated Microgrids. IEEE Transactions on Smart Grid, 9(5), 4004-4016. doi:10.1109/TSG.2016.2646779

  6. Kundur, D., Contreras, J., Srinivasan, D., Gatsis, N., Wang, S., & Peeta, S. (2018). Introduction to the Issue on Signal and Information Processing for Critical Infrastructures. IEEE Journal on Selected Topics in Signal Processing, 12(4), 575-577. doi:10.1109/JSTSP.2018.2852118

  7. Zhang, W., Quan, H., & Srinivasan, D. (2018). An Improved Quantile Regression Neural Network for Probabilistic Load Forecasting. IEEE Transactions on Smart Grid. doi:10.1109/TSG.2018.2859749

  8. Gandhi, O., Rodriguez-Gallegos, C. D., Gorla, N. B., Bieri, M., Reindl, T., & Srinivasan, D. (2018). Reactive Power Cost from PV Inverters Considering Inverter Lifetime Assessment. IEEE Transactions on Sustainable Energy. doi:10.1109/TSTE.2018.2846544

  9. Verma, P. P., Srinivasan, D., Swarup, K. S., & Mehta, R. (2018). A Review of Uncertainty Handling Techniques in Smart Grid. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, 26(3), 345-378. doi:10.1142/S0218488518500186

  10. Pillay, N., Qu, R., Srinivasan, D., Hammer, B., & Sörensen, K. (2018). Automated Design of Machine Learning and Search Algorithms [Guest Editorial]. IEEE Computational Intelligence Magazine, 13(2), 16-17. doi:10.1109/MCI.2018.2806988

  11. Kumar, D. S., Srinivasan, D., Sharma, A., & Reindl, T. (2018). Adaptive directional overcurrent relaying scheme for meshed distribution networks. IET Generation, Transmission and Distribution, 12(13), 3212-3220. doi:10.1049/iet-gtd.2017.1279

  12. Gandhi, O., Zhang, W., Rodriguez-Gallegos, C. D., Bieri, M., Reindl, T., & Srinivasan, D. (2018). Analytical Approach to Reactive Power Dispatch and Energy Arbitrage in Distribution Systems with DERs. IEEE Transactions on Power Systems. doi:10.1109/TPWRS.2018.2829527

  13. Wang, Y., Hu, Q., Srinivasan, D., & Wang, Z. (2018). Wind Power Curve Modeling and Wind Power Forecasting with Inconsistent Data. IEEE Transactions on Sustainable Energy. doi:10.1109/TSTE.2018.2820198

  14. Senthil kumar, J., Charles Raja, S., Srinivasan, D., & Venkatesh, P. (2018). Hybrid renewable energy-based distribution system for seasonal load variations. International Journal of Energy Research, 42(3), 1066-1087. doi:10.1002/er.3902

  15. Utkarsh, K., Srinivasan, D., Trivedi, A., Zhang, W., & Reindl, T. (2018). Distributed Model-predictive Real-time Optimal Operation of a Network of Smart Microgrids. IEEE Transactions on Smart Grid. doi:10.1109/TSG.2018.2810897

  16. Bi, Y., Lu, X., Sun, Z., Srinivasan, D., & Sun, Z. (2018). Optimal Type-2 Fuzzy System for Arterial Traffic Signal Control. IEEE Transactions on Intelligent Transportation Systems, 19(9), 3009-3027. doi:10.1109/TITS.2017.2762085

  17. Bal, S., Yelaverthi, D. B., Rathore, A. K., & Srinivasan, D. (2018). Improved Modulation Strategy Using Dual Phase Shift Modulation for Active Commutated Current-Fed Dual Active Bridge. IEEE Transactions on Power Electronics, 33(9), 7359-7375. doi:10.1109/TPEL.2017.2764917

  18. Nunna, H. S. V. S. K., & Srinivasan, D. (2017). Multiagent-Based Transactive Energy Framework for Distribution Systems With Smart Microgrids. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 13(5), 2241-2250. doi:10.1109/TII.2017.2679808

  19. Mehta, R., Srinivasan, D., Trivedi, A., & Yang, J. (2017). Hybrid Planning Method Based on Cost-Benefit Analysis for Smart Charging of Plug-in Electric Vehicles in Distribution Systems. IEEE Transactions on Smart Grid. doi:10.1109/TSG.2017.2746687

  20. Zhang, D., Nguang, S. K., Srinivasan, D., & Yu, L. (2018). Distributed Filtering for Discrete-Time T-S Fuzzy Systems With Incomplete Measurements. IEEE Transactions on Fuzzy Systems, 26(3), 1459-1471. doi:10.1109/TFUZZ.2017.2725228

  21. Zhang, D., Xu, Z., Srinivasan, D., & Yu, L. (2017). Leader-Follower Consensus of Multiagent Systems With Energy Constraints: A Markovian System Approach. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 47(7), 1727-1736. doi:10.1109/TSMC.2017.2677471

  22. Gnanasambandam, K., Edpuganti, A., Rathore, A. K., & Srinivasan, D. (2017). Modified Synchronous Pulsewidth Modulation of Current-Fed Five-Level Inverter for Solar Integration. IEEE TRANSACTIONS ON POWER ELECTRONICS, 32(5), 3370-3381. doi:10.1109/TPEL.2016.2585584

  23. Srinivasan, D., Rajgarhia, S., Radhakrishnan, B. M., Sharma, A., & Khincha, H. P. (2017). Game-Theory based dynamic pricing strategies for demand side management in smart grids. ENERGY, 126, 132-143. doi:10.1016/j.energy.2016.11.142

  24. Gnanasambandam, K., Rathore, A. K., Edpuganti, A., Srinivasan, D., & Rodriguez, J. (2017). Current-Fed Multilevel Converters: An Overview of Circuit Topologies, Modulation Techniques, and Applications. IEEE TRANSACTIONS ON POWER ELECTRONICS, 32(5), 3382-3401. doi:10.1109/TPEL.2016.2585576

  25. Shang, C., Srinivasan, D., & Reindl, T. (2017). Generation and storage scheduling of combined heat and power. ENERGY, 124, 693-705. doi:10.1016/j.energy.2017.02.038

  26. Zhang, D., Wang, Q. G., Srinivasan, D., Li, H., & Yu, L. (2018). Asynchronous state estimation for discrete-time switched complex networks with communication constraints. IEEE Transactions on Neural Networks and Learning Systems, 29(5), 1732-1746. doi:10.1109/TNNLS.2017.2678681

  27. Suganya, S., Charles Raja, S., Srinivasan, D., & Venkatesh, P. (2018). Smart utilization of renewable energy sources in a microgrid system integrated with plug-in hybrid electric vehicles. International Journal of Energy Research, 42(3), 1210-1224. doi:10.1002/er.3921

  28. Gandhi, O., Rodriguez-Gallegos, C. D., Zhang, W., Srinivasan, D., & Reindl, T. (2018). Economic and technical analysis of reactive power provision from distributed energy resources in microgrids. APPLIED ENERGY, 210, 827-841. doi:10.1016/j.apenergy.2017.08.154

  29. Zhang, D., Srinivasan, D., Yu, L., Zhang, W. -A., & Xing, K. (2016). Distributed non-fragile filtering in sensor networks with energy constraints. INFORMATION SCIENCES, 370, 695-707. doi:10.1016/j.ins.2016.05.006

  30. Gnanasambandam, K., Edpuganti, A., Rathore, A. K., Srinivasan, D., Cecati, C., & Buccella, C. (2016). Optimal Low Switching Frequency Pulsewidth Modulation of Current-Fed Three-Level Converter for Solar Power Integration. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 63(11), 6877-6886. doi:10.1109/TIE.2016.2586019

  31. Shang, C., Srinivasan, D., & Reindl, T. (2016). Generation-scheduling-coupled battery sizing of stand-alone hybrid power, systems. ENERGY, 114, 671-682. doi:10.1016/j.energy.2016.07.123

  32. Radhakrishnan, B. M., Srinivasan, D., & Mehta, R. (2016). Fuzzy-Based Multi-Agent System for Distributed Energy Management in Smart Grids. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 24(5), 781-803. doi:10.1142/S0218488516500355

  33. Shang, C., Srinivasan, D., & Reindl, T. (2016). Economic and Environmental Generation and Voyage Scheduling of All-Electric Ships. IEEE TRANSACTIONS ON POWER SYSTEMS, 31(5), 4087-4096. doi:10.1109/TPWRS.2015.2498972

  34. Srinivasan, D., & Venayagamoorthy, G. K. (2016). Special Issue on "Neural Networks and Learning Systems Applications in Smart Grid". IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 27(8), 1601-1603. doi:10.1109/TNNLS.2016.2545560

  35. Trivedi, A., Srinivasan, D., Biswas, S., & Reindl, T. (2016). A genetic algorithm - differential evolution based hybrid framework: Case study on unit commitment scheduling problem. INFORMATION SCIENCES, 354, 275-300. doi:10.1016/j.ins.2016.03.023

  36. Shang, C., Srinivasan, D., & Reindl, T. (2016). An improved particle swarm optimisation algorithm applied to battery sizing for stand-alone hybrid power systems. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 74, 104-117. doi:10.1016/j.ijepes.2015.07.009

  37. Nunna, H. S. V. S. K., Saklani, A. M., Sesetti, A., Battula, S., Doolla, S., & Srinivasan, D. (2016). Multi-agent based Demand Response management system for combined operation of smart microgrids. SUSTAINABLE ENERGY GRIDS & NETWORKS, 6, 25-34. doi:10.1016/j.segan.2016.01.002

  38. Srinivasan, D., Trung, T., & Singh, C. (2016). Bidding and Cooperation Strategies for Electricity Buyers in Power Markets. IEEE SYSTEMS JOURNAL, 10(2), 422-433. doi:10.1109/JSYST.2014.2329314

  39. Quan, H., Srinivasan, D., & Khosravi, A. (2016). Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study. ENERGY, 103, 735-745. doi:10.1016/j.energy.2016.03.007

  40. Zhang, D., Yang, F., Yu, C., Srinivasan, D., & Yu, L. (2017). Robust fuzzy-model-based filtering for nonlinear networked systems with energy constraints. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 354(4), 1957-1973. doi:10.1016/j.jfranklin.2016.12.019

  41. Arokiasami, W. A., Vadakkepat, P., Tan, K. C., & Srinivasan, D. (2016). Interoperable multi-agent framework for unmanned aerial/ground vehicles: towards robot autonomy. COMPLEX & INTELLIGENT SYSTEMS, 2(1), 45-59. doi:10.1007/s40747-016-0014-8

  42. Kumar, D. S., Srinivasan, D., & Reindl, T. (2016). A Fast and Scalable Protection Scheme for Distribution Networks With Distributed Generation. IEEE TRANSACTIONS ON POWER DELIVERY, 31(1), 67-75. doi:10.1109/TPWRD.2015.2464107

  43. Mehta, R., Srinivasan, D., Khambadkone, A. M., Yang, J., & Trivedi, A. (2018). Smart charging strategies for optimal integration of plug-in electric vehicles within existing distribution system infrastructure. IEEE Transactions on Smart Grid, 9(1), 299-312. doi:10.1109/TSG.2016.2550559

  44. Bal, S., Rathore, A. K., & Srinivasan, D. (2016). Naturally Clamped Snubberless Soft-Switching Bidirectional Current-Fed Three-Phase Push-Pull DC/DC Converter for DC Microgrid Application. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 52(2), 1577-1587. doi:10.1109/TIA.2015.2487444

  45. Trivedi, A., Srinivasan, D., Sanyal, K., & Ghosh, A. (2017). A Survey of Multiobjective Evolutionary Algorithms Based on Decomposition. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 21(3), 440-462. doi:10.1109/TEVC.2016.2608507

  46. Radhakrishnan, B. M., & Srinivasan, D. (2016). A multi-agent based distributed energy management scheme for smart grid applications. ENERGY, 103, 192-204. doi:10.1016/j.energy.2016.02.117

  47. Sharma, A., Srinivasan, D., & Trivedi, A. (2018). A Decentralized Multi-Agent Approach for Service Restoration in Uncertain Environment. IEEE Transactions on Smart Grid, 9(4), 3394-3405. doi:10.1109/TSG.2016.2631639

  48. Trivedi, A., Srinivasan, D., Pal, K., Saha, C., & Reindl, T. (2015). Enhanced Multiobjective Evolutionary Algorithm Based on Decomposition for Solving the Unit Commitment Problem. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 11(6), 1346-1357. doi:10.1109/TII.2015.2485520

  49. Sharma, A., Srinivasan, D., & Trivedi, A. (2015). A Decentralized Multiagent System Approach for Service Restoration Using DG Islanding. IEEE TRANSACTIONS ON SMART GRID, 6(6), 2784-2793. doi:10.1109/TSG.2015.2418334

  50. Quan, H., Srinivasan, D., & Khosravi, A. (2015). Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 26(9), 2123-2135. doi:10.1109/TNNLS.2014.2376696

  51. Quan, H., Srinivasan, D., Khambadkone, A. M., & Khosravi, A. (2015). A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources. APPLIED ENERGY, 152, 71-82. doi:10.1016/j.apenergy.2015.04.103

  52. Khosravi, A., Nahavandi, S., Srinivasan, D., & Khosravi, R. (2015). Constructing Optimal Prediction Intervals by Using Neural Networks and Bootstrap Method. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 26(8), 1810-1815. doi:10.1109/TNNLS.2014.2354418

  53. Bal, S., Rathore, A. K., & Srinivasan, D. (2015). Modular Snubberless Bidirectional Soft-Switching Current-Fed Dual 6-Pack (CFD6P) DC/DC Converter. IEEE TRANSACTIONS ON POWER ELECTRONICS, 30(2), 519-523. doi:10.1109/TPEL.2014.2333771

  54. Sun, Z., Wang, N., Bi, Y., & Srinivasan, D. (2015). Parameter identification of PEMFC model based on hybrid adaptive differential evolution algorithm. ENERGY, 90, 1334-1341. doi:10.1016/j.energy.2015.06.081

  55. Bal, S., Rathore, A. K., & Srinivasan, D. (2015). Naturally Clamped Snubberless Soft-Switching Bidirectional Current-fed Three-Phase Push-Pull DC/DC Converter for DC Micro-grid Application. 2015 THIRTIETH ANNUAL IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION (APEC 2015), 717-724.

  56. Logenthiran, T., & Srinivasan, D. (2015). Multi-agent system for managing distributed energy storage and electrical vehicles. INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 9(2), 181-190. doi:10.3233/IDT-140215

  57. Trivedi, A., Srinivasan, D., Biswas, S., & Reindl, T. (2015). Hybridizing genetic algorithm with differential evolution for solving the unit commitment scheduling problem. SWARM AND EVOLUTIONARY COMPUTATION, 23, 50-64. doi:10.1016/j.swevo.2015.04.001

  58. Bi, Y., Srinivasan, D., Lu, X., Sun, Z., & Zeng, W. (2014). Type-2 fuzzy multi-intersection traffic signal control with differential evolution optimization. EXPERT SYSTEMS WITH APPLICATIONS, 41(16), 7338-7349. doi:10.1016/j.eswa.2014.06.022 (Netherlands).

  59. Quan, H., Srinivasan, D., & Khosravi, A. (2014). Uncertainty handling using neural network-based prediction intervals for electrical load forecasting. ENERGY, 73, 916-925. doi:10.1016/j.energy.2014.06.104

  60. Quan, H., Srinivasan, D., & Khosravi, A. (2014). Particle swarm optimization for construction of neural network-based prediction intervals. NEUROCOMPUTING, 127, 172-180. doi:10.1016/j.neucom.2013.08.020

  61. Quan, H., Srinivasan, D., & Khosravi, A. (2014). Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 25(2), 303-315. doi:10.1109/TNNLS.2013.2276053

  62. Sun, Z., Wang, N., Srinivasan, D., & Bi, Y. (2014). Optimal tunning of type-2 fuzzy logic power system stabilizer based on differential evolution algorithm. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 62, 19-28. doi:10.1016/j.ijepes.2014.04.022

  63. Zhao, X., Xu, J., & Srinivasan, D. (2014). Novel and efficient local coordinated freeway ramp metering strategy with simultaneous perturbation stochastic approximation-based parameter learning. IET INTELLIGENT TRANSPORT SYSTEMS, 8(7), 581-589. doi:10.1049/iet-its.2012.0192

  64. Balaji, P. G., & Srinivasan, D. (2014). Modified Symbiotic Evolutionary Learning for Type-2 Fuzzy System. IEEE SYSTEMS JOURNAL, 8(2), 353-362. doi:10.1109/JSYST.2013.2247192

  65. Enhanced Multiobjective Evolutionary Algorithm based on Decomposition for Solving the Unit Commitment Problem. (2014). CoRR, abs/1410.4343.

  66. J66. Logenthiran, T., Srinivasan, D., & Vanessa, K. W. M. (2014). Demand side management of smart grid: Load shifting and incentives. JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 6(3), 18 pages. doi:10.1063/1.4885106

  67. Sharma, D., Trivedi, A., Srinivasan, D., & Thillainathan, L. (2013). Multi-agent modeling for solving profit based unit commitment problem. APPLIED SOFT COMPUTING, 13(8), 3751-3761. doi:10.1016/j.asoc.2013.04.001

  68. Sharma, V., & Srinivasan, D. (2013). A hybrid intelligent model based on recurrent neural networks and excitable dynamics for price prediction in deregulated electricity market. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 26(5-6), 1562-1574. doi:10.1016/j.engappai.2012.12.012

  69. Xu, J., Zhao, X., & Srinivasan, D. (2013). On optimal freeway local ramp metering using fuzzy logic control with particle swarm optimisation. IET INTELLIGENT TRANSPORT SYSTEMS, 7(1), 95-104. doi:10.1049/iet-its.2012.0087

  70. Trivedi, A., Srinivasan, D., Sharma, D., & Singh, C. (2013). Evolutionary Multi-Objective Day-Ahead Thermal Generation Scheduling in Uncertain Environment. IEEE TRANSACTIONS ON POWER SYSTEMS, 28(2), 1345-1354. doi:10.1109/TPWRS.2012.2222939

  71. Logenthiran, T., & Srinivasan, D. (2012). Optimal selection and sizing of distributed energy resources for distributed power systems. JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 4(5), 18 pages. doi:10.1063/1.4757618

  72. Logenthiran, T., Srinivasan, D., & Shun, T. Z. (2012). Demand Side Management in Smart Grid Using Heuristic Optimization. IEEE TRANSACTIONS ON SMART GRID, 3(3), 1244-1252. doi:10.1109/TSG.2012.2195686

  73. Logenthiran, T., Srinivasan, D., Khambadkone, A. M., & Aung, H. N. (2012). Multiagent System for Real-Time Operation of a Microgrid in Real-Time Digital Simulator. IEEE TRANSACTIONS ON SMART GRID, 3(2), 925-933. doi:10.1109/TSG.2012.2189028

  74. Khosravi, A., Nahavandi, S., Creighton, D., & Srinivasan, D. (2012). Interval Type-2 Fuzzy Logic Systems for Load Forecasting: A Comparative Study. IEEE TRANSACTIONS ON POWER SYSTEMS, 27(3), 1274-1282. doi:10.1109/TPWRS.2011.2181981

  75. Pindoriya, N. M., Jirutitijaroen, P., Srinivasan, D., & Singh, C. (2011). Composite Reliability Evaluation Using Monte Carlo Simulation and Least Squares Support Vector Classifier. IEEE TRANSACTIONS ON POWER SYSTEMS, 26(4), 2483-2490. doi:10.1109/TPWRS.2011.2116048

  76. Yadav, V., & Srinivasan, D. (2011). A SOM-based hybrid linear-neural model for short-term load forecasting. NEUROCOMPUTING, 74(17), 2874-2885. doi:10.1016/j.neucom.2011.03.039

  77. Balaji, P. G., & Srinivasan, D. (2011). Type-2 fuzzy logic based urban traffic management. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 24(1), 12-22. doi:10.1016/j.engappai.2010.08.007

  78. Logenthiran, T., Srinivasan, D., & Khambadkone, A. M. (2011). Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system. ELECTRIC POWER SYSTEMS RESEARCH, 81(1), 138-148. doi:10.1016/j.epsr.2010.07.019

  79. Balaji, P. G., & Srinivasan, D. (2010). Multi-Agent System in Urban Traffic Signal Control. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 5(4), 43-51. doi:10.1109/MCI.2010.938363

  80. Srinivasan, D., & Choy, M. C. (2010). Hybrid multi-agent systems. Studies in Computational Intelligence, 310, 29-42. doi:10.1007/978-3-642-14435-6_2

  81. Balaji, P. G., & Srinivasan, D. (2010). An introduction to multi-agent systems. Studies in Computational Intelligence, 310, 1-27. doi:10.1007/978-3-642-14435-6_1

  82. Balaji, P. G., German, X., & Srinivasan, D. (2010). Urban traffic signal control using reinforcement learning agents. IET INTELLIGENT TRANSPORT SYSTEMS, 4(3), 177-188. doi:10.1049/iet-its.2009.0096

  83. Gokulan, B. P., & Srinivasan, D. (2010). Distributed Geometric Fuzzy Multiagent Urban Traffic Signal Control. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 11(3), 714-727. doi:10.1109/TITS.2010.2050688

  84. Rachmawati, L., & Srinivasan, D. (2010). Incorporating the Notion of Relative Importance of Objectives in Evolutionary Multiobjective Optimization. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 14(4), 530-546. doi:10.1109/TEVC.2009.2036162

  85. Srinivasan, D., Howlett, R. J., Lovrek, I., Jain, L. C., & Lim, C. -P. (2010). Design and application of neural networks and intelligent learning systems. NEUROCOMPUTING, 73(4-6), 591-592. doi:10.1016/j.neucom.2009.11.003

  86. Deng, H., Srinivasan, D., & Oruganti, R. (2010). A B-spline network based neural controller for power electronic applications. NEUROCOMPUTING, 73(4-6), 593-601. doi:10.1016/j.neucom.2009.10.019

  87. Srinivasan, D. (2009). Experience Teaching A Graduate Level Course in Evolutionary Computation. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 4(3), 45-46. doi:10.1109/MCI.2009.933100

  88. Rachmawati, L., & Srinivasan, D. (2009). Multiobjective Evolutionary Algorithm With Controllable Focus on the Knees of the Pareto Front. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 13(4), 810-824. doi:10.1109/TEVC.2009.2017515

  89. Srinivasan, D., Chan, C. W., & Balaji, P. G. (2009). Computational intelligence-based congestion prediction for a dynamic urban street network. NEUROCOMPUTING, 72(10-12), 2710-2716. doi:10.1016/j.neucom.2009.01.005

  90. Srinivasan, D., & Hua, Z. (2009). Solving time-tabling problems using evolutionary algorithms and heuristics search. Studies in Computational Intelligence, 171, 53-69. doi:10.1007/978-3-540-88051-6_3

  91. Srinivasan, D. (2008). Energy demand prediction using GMDH networks. NEUROCOMPUTING, 72(1-3), 625-629. doi:10.1016/j.neucom.2008.08.006

  92. Srinivasan, D., & Woo, D. (2008). Evolving cooperative bidding strategies in a power market. APPLIED INTELLIGENCE, 29(2), 162-173. doi:10.1007/s10489-007-0050-6

  93. Srinivasan, D., & Rachmawati, L. (2008). Efficient Fuzzy Evolutionary Algorithm-Based Approach for Solving the Student Project Allocation Problem. IEEE TRANSACTIONS ON EDUCATION, 51(4), 439-447. doi:10.1109/TE.2007.912537

  94. Srinivasan, D., Sharma, V., & Toh, K. A. (2008). Reduced multivariate polynomial-based neural network for automated traffic incident detection. NEURAL NETWORKS, 21(2-3), 484-492. doi:10.1016/j.neunet.2007.12.028

  95. Deng, H., Oruganti, R., & Srinivasan, D. (2008). Neural controller for UPS inverters based on B-spline network. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 55(2), 899-909. doi:10.1109/TIE.2007.909064

  96. Deng, H., Oruganti, R., & Srinivasan, D. (2008). A simple control method for high-performance UPS inverters through output-impedance reduction. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 55(2), 888-898. doi:10.1109/TIE.2007.909053

  97. Srinivasan, D., Sanyal, S., & Sharma, V. (2007). Freeway incident detection using hybrid fuzzy neural network. IET INTELLIGENT TRANSPORT SYSTEMS, 1(4), 249-259. doi:10.1049/iet-its:20070003

  98. Srinivasan, D., & Choy, M. C. (2007). Distributed problem solving using evolutionary learning in multi-agent systems. Studies in Computational Intelligence, 66, 211-227. doi:10.1007/978-3-540-72377-6_9

  99. Toh, K. -A., Tran, Q. -L., & Srinivasan, D. (2007). Hyperbolic function networks for pattern classification. TRENDS IN NEURAL COMPUTATION, 35, 1-8.

  100. Choy, M. C., Srinivasan, D., & Cheu, R. L. (2006). Neural networks for continuous online learning and control. IEEE TRANSACTIONS ON NEURAL NETWORKS, 17(6), 1511-1531. doi:10.1109/TNN.2006.881710

  101. Srinivasan, D., & Choy, M. C. (2006). Cooperative multi-agent system for coordinated traffic signal control. IEE Proceedings: Intelligent Transport Systems, 153(1), 41-50. doi:10.1049/ip-its:20055011

  102. Srinivasan, D., Choy, M. C., & Cheu, R. L. (2006). Neural networks for real-time traffic signal control. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 7(3), 261-272. doi:10.1109/TITS.2006.874716

  103. Srinivasan, D., Ng, W. S., & Liew, A. C. (2006). Neural-network-based signature recognition for harmonic source identification. IEEE TRANSACTIONS ON POWER DELIVERY, 21(1), 398-405. doi:10.1109/TPWRD.2005.852370

  104. Viswanathan, K., Oruganti, R., & Srinivasan, D. (2005). Nonlinear function controller: A simple alternative to fuzzy logic controller for a power electronic converter. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 52(5), 1439-1448. doi:10.1109/TIE.2005.855652

  105. Tran, Q. L., Toh, K. A., Srinivasan, D., Wong, K. L., & Low, S. Q. C. (2005). An empirical comparison of nine pattern classifiers. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 35(5), 1079-1091. doi:10.1109/TSMCB.2005.847745

  106. Srinivasan, D., & Feng, W. C. (2005). Performance analysis of multi-dimensional packet classification on programmable network processors. COMPUTER COMMUNICATIONS, 28(15), 1752-1760. doi:10.1016/j.comcom.2004.12.019

  107. Viswanathan, K., Oruganti, R., & Srinivasan, D. (2005). Dual-mode control of tri-state boost converter for improved performance. IEEE TRANSACTIONS ON POWER ELECTRONICS, 20(4), 790-797. doi:10.1109/TPEL.2005.850907

  108. Deng, H., Oruganti, R., & Srinivasan, D. (2005). PWM methods to handle time delay in digital control of a UPS inverter. IEEE Power Electronics Letters, 3(1), 1-6. doi:10.1109/LPEL.2004.842402

  109. Srinivasan, D., Jin, X., & Cheu, R. L. (2005). Adaptive neural network models for automatic incident detection on freeways. NEUROCOMPUTING, 64, 473-496. doi:10.1016/j.neucom.2004.12.001

  110. Toh, K. A., Tran, Q. L., & Srinivasan, D. (2004). Benchmarking a reduced multivariate polynomial pattern classifier. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 26(6), 740-755. doi:10.1109/TPAMI.2004.3

  111. Srinivasan, D., Jin, X., & Cheu, R. L. (2004). Evaluation of adaptive neural network models for freeway incident detection. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 5(1), 1-11. doi:10.1109/TITS.2004.825084

  112. Choy, M. C., Srinivasan, D., & Cheu, R. L. (2003). Cooperative, hybrid agent architecture for real-time traffic signal control. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 33(5), 597-607. doi:10.1109/TSMCA.2003.817394

  113. Cheu, R. L., Srinivasan, D., & Lee, D. H. (2003). Guest editorial: IEEE 5th International Conference on Intelligent Transportation Systems Papers. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 4(2), 57-58. doi:10.1109/TITS.2003.821210

  114. Viswanathan, K., Oruganti, R., & Srinivasan, D. (2002). A novel tri-state boost converter with fast dynamics. IEEE TRANSACTIONS ON POWER ELECTRONICS, 17(5), 677-683. doi:10.1109/TPEL.2002.802197

  115. Jin, X., Cheu, R. L., & Srinivasan, D. (2002). Development and adaptation of constructive probabilistic neural network in freeway incident detection. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 10(2), 121-147. doi:10.1016/S0968-090X(01)00007-9

  116. Jin, X., Srinivasan, D., & Cheu, R. L. (2001). Classification of freeway traffic patterns for incident detection using constructive probabilistic neural networks. IEEE TRANSACTIONS ON NEURAL NETWORKS, 12(5), 1173-1187. doi:10.1109/72.950145

  117. Srinivasan, D., Cheu, R. L., Poh, Y. P., & Ng, A. K. C. (2000). Automated fault detection in power distribution networks using a hybrid fuzzy-genetic algorithm approach. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 13(4), 407-418. doi:10.1016/S0952-1976(00)00012-9

  118. JToh, K. A., Tran, Q. L., & Srinivasan, D. (2004). Benchmarking a reduced multivariate polynomial pattern classifier. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 26(6), 740-755. doi:10.1109/TPAMI.2004.3

  119. Srinivasan, D., Cheu, R. L., Poh, Y. P., & Ng, A. K. C. (2000). Development of an intelligent technique for traffic network incident detection. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 13(3), 311-322. doi:10.1016/S0952-1976(00)00011-7

  120. hang, C. S., Low, J. S., & Srinivasan, D. (1999). Application of tabu search in optimal system design and operation of MRT power supply systems. IEE PROCEEDINGS-ELECTRIC POWER APPLICATIONS, 146(1), 75-80. doi:10.1049/ip-epa:19990214

  121. Srinivasan, D., Liew, A. C., & Lim, K. L. (1999). Application of evolutionary computation for machine design optimization. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 7(3), 127-130.
  122. Srinivasan, D., Tan, S. S., Chang, C. S., & Chan, E. K. (1999). Parallel neural network-fuzzy expert system strategy for short-term load forecasting: System implementation and performance evaluation - Discussion. IEEE TRANSACTIONS ON POWER SYSTEMS, 14(3), 1106.

  123. Srinivasan, D., Tan, S. S., Chang, C. S., & Chan, E. K. (1999). Parallel neural network-fuzzy expert system strategy for short-term load forecasting: System implementation and performance evaluation. IEEE TRANSACTIONS ON POWER SYSTEMS, 14(3), 1100-1105. doi:10.1109/59.780934

  124. Srinivasan, D. (1998). Evolving artificial neural networks for short term load forecasting. NEUROCOMPUTING, 23(1-3), 265-276. doi:10.1016/S0925-2312(98)00074-5

  125. Heng, E. T. H., Srinivasan, D., & Liew, A. C. (1998). Short term load forecasting using genetic algorithm and neural networks. PROCEEDINGS OF EMPD '98 - 1998 INTERNATIONAL CONFERENCE ON ENERGY MANAGEMENT AND POWER DELIVERY, VOLS 1 AND 2 AND SUPPLEMENT, 576-581.

  126. Srinivasan, D., Tan, S. S., Chang, C. S., & Chan, E. K. (1998). Practical implementation of a hybrid fuzzy neural network for one-day-ahead load forecasting. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 145(6), 687-692. doi:10.1049/ip-gtd:19982363

  127. Srinivasan, D., Chang, C. S., Liew, A. C., & Leong, K. C. (1998). Power system security assessment and enhancement using artificial neural network. PROCEEDINGS OF EMPD '98 - 1998 INTERNATIONAL CONFERENCE ON ENERGY MANAGEMENT AND POWER DELIVERY, VOLS 1 AND 2 AND SUPPLEMENT, 582-587.

  128. Cheu, R. L., Jin, X., Ng, K. C., Ng, Y. L., & Srinivasan, D. (1998). Calibration of FRESIM for Singapore Expressway using genetic algorithm. JOURNAL OF TRANSPORTATION ENGINEERING-ASCE, 124(6), 526-535. doi:10.1061/(ASCE)0733-947X(1998)124:6(526)

  129. Chang, C. S., Chen, J. M., Srinivasan, D., Wen, F. S., & Liew, A. C. (1997). Fuzzy logic approach in power system fault section identification. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 144(5), 406-414. doi:10.1049/ip-gtd:19971278

  130. Chang, C. S., Chen, J. M., Liew, A. C., Srinivasan, D., & Wen, F. S. (1997). Fuzzy expert system for fault diagnosis in power systems. ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 5(2), 75-81.

  131. Srinivasan, D., & Tettamanzi, A. G. B. (1997). An evolutionary algorithm for evaluation of emission compliance options in view of the clean air act amendments. IEEE Power Engineering Review, 17(2), 64.

  132. Srinivasan, D., & Tettamanzi, A. G. B. (1997). An evolutionary algorithm for evaluation of emission compliance options in view of the Clean Air Act Amendments. IEEE TRANSACTIONS ON POWER SYSTEMS, 12(1), 336-341. doi:10.1109/59.574956

  133. Miranda, V., Srinivasan, D., & Proenca, L. M. (1998). Evolutionary computation in power systems. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 20(2), 89-98. doi:10.1016/S0142-0615(97)00040-9

  134. Srinivasan, D., & Tettamanzi, A. (1996). Heuristics-guided evolutionary approach to multiobjective generation scheduling. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 143(6), 553-559. doi:10.1049/ip-gtd:19960627

  135. Srinivasan, D., & Hoole, S. R. H. (1996). Fuzzy multiobject optimization for the starting design of a magnetic circuit. IEEE TRANSACTIONS ON MAGNETICS, 32(3), 1230-1233. doi:10.1109/20.497466

  136. Srinivasan, D., Chang, C. S., & Liew, A. C. (1995). Demand Forecasting Using Fuzzy Neural Computation, With Special Emphasis On Weekend And Public Holiday Forecasting. IEEE TRANSACTIONS ON POWER SYSTEMS, 10(4), 1897-1903. doi:10.1109/59.476055

  137. Srinivasan, D., Liew, A. C., & Chang, C. S. (1995). Applications of fuzzy systems in power systems. ELECTRIC POWER SYSTEMS RESEARCH, 35(1), 39-43. doi:10.1016/0378-7796(95)00985-X

  138. Srinivasan, D., Liew, A. C., & Chang, C. S. (1994). Forecasting Daily Load Curves Using A Hybrid Fuzzy Neural Approach. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 141(6), 561-567. doi:10.1049/ip-gtd:19941288

  139. Srinivasan, D., Chang, C. S., & Liew, A. C. (1994). Multiobjective Generation Scheduling Using Fuzzy Optimal Search Technique. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 141(3), 233-242. doi:10.1049/ip-gtd:19949943

  140. Srinivasan, D., Liew, A. C., Chang, C. S., & Chen, J. S. P. (1994). Intelligent Operation Of Distribution Network. IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 141(2), 106-116. doi:10.1049/ip-gtd:19949769

  141. Chang, C. S., Srinivasan, D., & Liew, A. C. (1994). A Hybrid Model For Transient Stability Evaluation Of Interconnected Longitudinal Power-Systems Using Neural-Network Pattern-Recognition Approach - Reply. IEEE TRANSACTIONS ON POWER SYSTEMS, 9(1), 92.

  142. Srinivasan, D., Liew, A. C., & Chang, C. S. (1994). A Neural-Network Short-Term Load Forecaster. ELECTRIC POWER SYSTEMS RESEARCH, 28(3), 227-234. doi:10.1016/0378-7796(94)90037-X

  143. Chang, C. S., Srinivasan, D., & Liew, A. C. (1994). A Hybrid Model For Transient Stability Evaluation Of Interconnected Longitudinal Power-Systems Using Neural-Network Pattern-Recognition Approach. IEEE TRANSACTIONS ON POWER SYSTEMS, 9(1), 85-92. doi:10.1109/59.317554

  144. Srinivasan, D., Liew, A. C., & Chang, C. S. (1993). Integrated security constrained generation scheduling in an interconnected system using an IA approach. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, 1(2), 119-124.
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