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2020 – today
- 2024
[j24]Zhao Wei
, Teng Long, Kang Tai, Renhe Shi:
Metamodel-Based Multidisciplinary Design Optimization of Geostationary Debris Removal Satellites. IEEE Trans. Aerosp. Electron. Syst. 60(4): 4621-4639 (2024)- [c24]Xiuke Tang, Pradeep V. Mandapaka, Kang Tai, Edmond Yat-Man Lo:
Multi-regional urban systems vulnerability and disaster impact analysis. SysCon 2024: 1-8 - 2023
- [j23]Wenjie Chen, Kang Tai, Michael Wai Shing Lau, Ahmed Abdelhakim, Ricky Chan, Alf Kare Adnanes, Tegoeh Tjahjowidodo:
Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control. IEEE Access 11: 110342-110360 (2023) - [j22]Wenjie Chen, Kang Tai, Michael Wai Shing Lau, Ahmed Abdelhakim, Ricky Chan, Alf Kare Adnanes, Tegoeh Tjahjowidodo:
Optimal Power and Energy Management Control for Hybrid Fuel Cell-Fed Shipboard DC Microgrid. IEEE Trans. Intell. Transp. Syst. 24(12): 14133-14150 (2023) - 2021
- [j21]Akhila Kizhakkedath, Kang Tai:
Vulnerability analysis of critical infrastructure network. Int. J. Crit. Infrastructure Prot. 35: 100472 (2021) - 2020
- [j20]Chi Yung Lam, Kang Tai:
Network topological approach to modeling accident causations and characteristics: Analysis of railway incidents in Japan. Reliab. Eng. Syst. Saf. 193: 106626 (2020)
2010 – 2019
- 2019
- [j19]Jiwei Lin, Kang Tai, Robert Tiong Lee Kong, Mong Soon Sim:
Modelling critical infrastructure network interdependencies and failure. Int. J. Crit. Infrastructures 15(1): 1-23 (2019) - 2018
- [j18]Chi Yung Lam, Kang Tai:
Modeling infrastructure interdependencies by integrating network and fuzzy set theory. Int. J. Crit. Infrastructure Prot. 22: 51-61 (2018) - 2017
- [j17]Akhil Garg, Biranchi Narayan Panda, Kang Tai:
True stress measurement of nuclear fuel rod cladding material subjected to DSA regime. Neural Comput. Appl. 28(S-1): 119-126 (2017) - 2016
- [j16]Anand J. Kulkarni, Ishaan R. Kale, Kang Tai:
Probability collectives for solving discrete and mixed variable problems. Int. J. Comput. Aided Eng. Technol. 8(4): 325-361 (2016) - [j15]Anand J. Kulkarni, Neha S. Patankar, Kang Tai:
Constraint handling in probability collectives using a modified feasibility-based rule. Int. J. Comput. Sci. Eng. 13(4): 303-321 (2016) - [c23]Jiwei Lin, Kang Tai, Robert L. K. Tiong, Mong Soon Sim:
A General Framework for Critical Infrastructure Interdependencies Modeling Using Economic Input-Output Model and Network Analysis. CSDM Asia 2016: 59-74 - [c22]Chi Yung Lam, Kang Tai:
Resilience Analysis on Infrastructure Networks with Heterogeneous Nodes. CSDM 2016: 241 - 2015
- [b1]Anand Jayant Kulkarni, Kang Tai, Ajith Abraham:
Probability Collectives - A Distributed Multi-agent System Approach for Optimization. Intelligent Systems Reference Library 86, Springer 2015, ISBN 978-3-319-15999-7, pp. 1-144 - 2014
- [j14]Akhil Garg, Kang Tai:
Stepwise approach for the evolution of generalized genetic programming model in prediction of surface finish of the turning process. Adv. Eng. Softw. 78: 16-27 (2014) - [j13]Akhil Garg, Ankit Garg, Kang Tai, S. Sreedeep:
An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes. Eng. Appl. Artif. Intell. 30: 30-40 (2014) - [j12]Akhil Garg, V. Vijayaraghavan, S. S. Mahapatra, Kang Tai, C. H. Wong:
Performance evaluation of microbial fuel cell by artificial intelligence methods. Expert Syst. Appl. 41(4): 1389-1399 (2014) - [j11]Neha S. Patankar, Anand Jayant Kulkarni, Kang Tai, T. D. Ghate, A. R. Parvate:
Multi-criteria probability collectives. Int. J. Bio Inspired Comput. 6(6): 369-383 (2014) - [j10]Akhil Garg, Kang Tai, C. H. Lee, M. M. Savalani:
A hybrid \(\text{ M}5^\prime \) -genetic programming approach for ensuring greater trustworthiness of prediction ability in modelling of FDM process. J. Intell. Manuf. 25(6): 1349-1365 (2014) - [j9]Akhil Garg, V. Vijayaraghavan, C. H. Wong, Kang Tai, Liang Gao:
An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material. Simul. Model. Pract. Theory 44: 1-13 (2014) - [j8]Akhil Garg, V. Vijayaraghavan, C. H. Wong, Kang Tai, K. Sumithra, Liang Gao, Pravin M. Singru:
Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet. Simul. Model. Pract. Theory 48: 93-111 (2014) - [c21]Akhil Garg, Kang Tai:
An Improved Multi-Gene Genetic Programming Approach for the Evolution of Generalized Model in Modelling of Rapid Prototyping Process. IEA/AIE (1) 2014: 218-226 - 2013
- [j7]Chi Yung Lam, Jiaying Lin, Mong Soon Sim, Kang Tai:
Identifying vulnerabilities in critical infrastructures by network analysis. Int. J. Crit. Infrastructures 9(3): 190-210 (2013) - [j6]Akhil Garg, Kang Tai:
Comparison of statistical and machine learning methods in modelling of data with multicollinearity. Int. J. Model. Identif. Control. 18(4): 295-312 (2013) - [j5]Akhil Garg, Yogesh Bhalerao, Kang Tai:
Review of empirical modelling techniques for modelling of turning process. Int. J. Model. Identif. Control. 20(2): 121-129 (2013) - [c20]Akhila Kizhakkedath, Kang Tai, Mong Soon Sim, Robert Lee Kong Tiong, Jiaying Lin:
An Agent-Based Modeling and Evolutionary Optimization Approach for Vulnerability Analysis of Critical Infrastructure Networks. AsiaSim 2013: 176-187 - [c19]Akhil Garg, Kang Tai:
Selection of a robust experimental design for the effective modeling of nonlinear systems using Genetic Programming. CIDM 2013: 287-292 - [c18]Akhil Garg, S. Sriram, Kang Tai:
Empirical analysis of model selection criteria for genetic programming in modeling of time series system. CIFEr 2013: 90-94 - [c17]Akhil Garg, Kang Tai:
Genetic Programming for Modeling Vibratory Finishing Process: Role of Experimental Designs and Fitness Functions. SEMCCO (2) 2013: 23-31 - [p1]Anand J. Kulkarni, Kang Tai:
A Probability Collectives Approach for Multi-Agent Distributed and Cooperative Optimization with Tolerance for Agent Failure. Agent-Based Optimization 2013: 175-201 - 2012
- [c16]Anand J. Kulkarni, Neha S. Patankar, Amani Sandupatla, Kang Tai:
A modified feasibility-based rule for solving constrained optimization problems using Probability Collectives. HIS 2012: 213-218 - [c15]Anand J. Kulkarni, Ishaan R. Kale, Kang Tai, S. Kazemzadeh Azad:
Discrete optimization of truss structure using Probability Collectives. HIS 2012: 225-230 - 2011
- [j4]Anand J. Kulkarni, Kang Tai:
A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization. Appl. Comput. Intell. Soft Comput. 2011: 980216:1-980216:19 (2011) - [j3]Anand J. Kulkarni, Kang Tai:
Solving Constrained Optimization Problems Using Probability Collectives and a Penalty Function Approach. Int. J. Comput. Intell. Appl. 10(4): 445-470 (2011) - 2010
- [j2]Anand Jayant Kulkarni, Kang Tai:
Probability Collectives: A multi-agent approach for solving combinatorial optimization problems. Appl. Soft Comput. 10(3): 759-771 (2010) - [c14]Anand Jayant Kulkarni, Kang Tai:
Probability Collectives: A distributed optimization approach for constrained problems. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2008
- [c13]Kang Tai, Nianfeng F. Wang, Yaowen Yang:
Target geometry matching problem with conflicting objectives for multiobjective topology design optimization using GA. IEEE Congress on Evolutionary Computation 2008: 1873-1878 - [c12]Nianfeng F. Wang, Yaowen Yang, Kang Tai:
Optimization of structures under load uncertainties based on hybrid genetic algorithm. IEEE Congress on Evolutionary Computation 2008: 4039-4044 - [c11]Kang Tai, Nianfeng F. Wang, Yaowen Yang:
Hybrid GA multiobjective optimization for the design of compliant micro-actuators. SMC 2008: 559-564 - [c10]Nianfeng F. Wang, Yaowen Yang, Kang Tai:
Hybrid genetic algorithm for designing structures subjected to uncertainty. SMC 2008: 565-570 - [c9]Anand J. Kulkarni, Kang Tai:
Probability Collectives for decentralized, distributed optimization: A Collective Intelligence Approach. SMC 2008: 1271-1275 - 2007
- [j1]W. Liu, Kang Tai:
Optimal design of flat patterns for 3D folded structures by unfolding with topological validation. Comput. Aided Des. 39(10): 898-913 (2007) - [c8]Nianfeng F. Wang, Kang Tai:
A hybrid genetic algorithm for multiobjective structural optimization. IEEE Congress on Evolutionary Computation 2007: 2948-2955 - [c7]Shao Chong Oh, Chung Huat Tan, Fook Wai Kong, Yuan-Sin Tan, Khin Hua Ng, Gee Wah Ng, Kang Tai:
Multiobjective optimization of sensor network deployment by a genetic algorithm. IEEE Congress on Evolutionary Computation 2007: 3917-3921 - [c6]Nianfeng F. Wang, Kang Tai:
Handling objectives as adaptive constraints for multiobjective structural optimization. IEEE Congress on Evolutionary Computation 2007: 3922-3929 - [c5]Kang Tai, Nianfeng F. Wang:
An Enhanced Chromosome Encoding and Morphological Representation of Geometry for Structural Topology Optimization using GA. IEEE Congress on Evolutionary Computation 2007: 4178-4185 - 2003
- [c4]Kang Tai, Shamim Akhtar:
Development and testing of a morphological geometric representation scheme for topology design optimization using a genetic algorithm. IEEE Congress on Evolutionary Computation 2003: 655-662 - [c3]Sheng Yin Wang, Kang Tai:
A bit-array representation GA for structural topology optimization. IEEE Congress on Evolutionary Computation 2003: 671-677 - [c2]Kok Sung Won, Tapabrata Ray, Kang Tai:
A framework for optimization using approximate functions. IEEE Congress on Evolutionary Computation 2003: 1520-1527 - 2000
- [c1]Tapabrata Ray, Kang Tai, Seow Kian Chye:
An Evolutionary Algorithm for Constrained Optimization. GECCO 2000: 771-777
Coauthor Index
aka: Anand J. Kulkarni
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