SciELO - Scientific Electronic Library Online

Fen X., Lau F .C.M. Parallel Physics–Inspired Waterflow Particle Mechanics Algorithm for Load Rebalancing, Comput. Netw. 2010, doi:10.1016/j.comnet.2010.02.002. [ Links ]

Contet J., Franck G., Pablo G., Abder K. Physics Inspired Multiagent System for Vehicle Platooning. AAMAS'07, Honolulu, Hawaii, USA, 2007. [ Links ]

Li–Ping X., Zeng J.C. A Global Optimization Based on Physicomimetics Framework. GEC'09, June, 2009, Shanghai, China. [ Links ]

Richard A. Formato JD. Central Force Optimization: A New Nature Inspired Computational Framework for Multidimensional Search and Optimization. Nature Inspired Cooperative Strategies for Optimization (NICSO), 2008. 129, pp. 221–238. [ Links ]

Wang L., Li L.P. An Effective Hybrid Quantum–Inspired Evolutionary Algorithm for Parameter Estimation of Chaotic Systems. Expert Systems with Applications, 37:1279–1285, 2010. [ Links ]

Davies E.R. Machine Vision: Theory, Algorithms, Practicalities, Academic Press, London, 1990. [ Links ]

Muammar H., Nixon M. Approaches to Extending the Hough Transform., Proc. Int. Conference on Acoustics, Speech and Signal Processing ICASSP–89, 1989, 3, pp. 1556–1559. [ Links ]

Atherton T.J., Kerbyson D.J. Using Phase to Represent Radius in the Coherent Circle Hough Transform, Proc. IEE Colloquium on the Hough Transform, IEE, London, 1993. [ Links ]

Fischer M., Bolles R. Random Sample Consensus: A Paradigm to Model Fitting with Applications to Image Analysis and Automated Cartography. CACM, 24(6):381–395, 1981. [ Links ]

Shaked D., Yaron O. , Kiryati N. Deriving Stopping Rules for the Probabilistic Hough Transform by Sequential Analysis, Comput. Vision Image Understanding, 63:512–526, 1996. [ Links ]

Xu L., Oja E., Kultanen P. A New Curve Detection Method: Randomized Hough Transform (RHT). Pattern Recognition Lett, 11(5):331–338, 1990. [ Links ]

Han J.H., Koczy L.T., Poston T. Fuzzy Hough Transform, Proc. 2nd International Conference on Fuzzy Systems, 1993, 2, pp. 803808. [ Links ]

Lu W., Tan J.L. Detection of Incomplete Ellipse in Images with Strong Noise by Iterative Randomized Hough Transform (IRHT). Pattern Recognition, 41(4):1268–1279, 2008. [ Links ]

Roth G., Levine M.D. Geometric Primitive Extraction Using a Genetic Algorithm, IEEE Trans. Pattern Anal. Machine Intell, 16(9):901–905, 1994. [ Links ]

Lutton E., Martinez P. A Genetic Algorithm for the Detection 2–D Geometric Primitives on Images, Proc. of the 12th Internarional Conference on Pattern Recognition, 1994, 1, pp. 526–528. [ Links ]

Yao J., Kharma N., Grogono P. Fast Robust GA–Based Ellipse Detection, proc. 17th International Conference on Pattern Recognition ICPR–04, 2004, 2, Cambridge, UK, pp. 859–862. [ Links ]

Ayala–Ramírez V., García–Capulin C., Pérez–García A., Sánchez–Yáñez E. Circle Detection on Images Using Genetic Algorithms. Pattern Recognition Letters, 27(6):652–657, 2006. [ Links ]

Dasgupta S., Das S., Biswas A. Abraham A. Automatic Circle Detection on Digital Images whit an Adaptive Bacterial Forganging Algorithm. Soft Computing, 2009, DOI 10.1007/ s00500–009–0508–z. [ Links ]

Rosin P.L., Nyongesa H.O. Combining Evolutionary, Connectionist and Fuzzy Classification Algorithms for Shape Analysis, Cagnoni S. et al. (Eds.), Proc. EvoIASP, Real–World Applications of Evolutionary Computing, 2000, pp. 87–96. [ Links ]

Rosin P.L. Further Five Point Fit Ellipse Fitting, Proc. 8th British Machine Vision Conference, Cochester, UK, 1997, pp. 290–299. [ Links ]

Ilker–Birbil S., Shu–Cherng F. An Electromagnetism–Like Mechanism for Global Optimization. Journal of Global Optimization, 25:263–282, 2003. [ Links ]

Ilker–Birbil S., Shu–Cherng F., Sheu R.L. On the Convergence of a Population–Based Global Optimization Algorithm. Journal of Global Optimization, 30(2):301–318, 2004. [ Links ]

Rocha A., Fernández E. Hybridizing the Electromagnetism–Like Algorithm with Descent Search for Solving Engineering Design Problems. International Journal of Computer Mathematics, 86(10):1932–1946, 2009. [ Links ]

Rocha A., Fernández E. Modified Movement Force Vector in an Electromagnetism–Like Mechanism for Global Optimization. Optimization Methods & Software, 24(2):253–270, 2009. [ Links ]

Naderi B., Tavakkoli–Moghaddam R., Khalili M. Electromagnetism–Like Mechanism and Simulated Annealing Algorithms for Flowshop Scheduling Problems Minimizing the Total Weighted Tardiness and Makespan. Knowledge–Based Systems, 23(2):77–85, 2010. [ Links ]

Tsou C.S., Kao C.H. Multi–Objective Inventory Control Using Electromagnetism–Like Meta–Heuristic. International Journal of Production Research, 46(14):3859–3874, 2008. [ Links ]

Yurtkuran A., Emel E. A New Hybrid Electromagnetism–Like Algorithm for Capacitated Vehicle Routing Problems. Expert Systems with Applications, 37(4):3427–3433, 2010. [ Links ]

Jhen–Yan J., Kun–Chou L. Array Pattern Optimization Using Electromagnetism–Like Algorithm. AEU–International Journal of Electronics and Communications, 63(6):491–496, 2009. [ Links ]

Cowan E.W. Basic Electromagnetism, Academic Press, New York, 1968. [ Links ]

Fischer M., Bolles R. Random Sample Consensus: A Paradigm to Model Fitting with Applications to Image Analysis and Automated Cartography. CACM, 24(6):381–395, 1981. [ Links ]

Bresenham J.E. A Linear Algorithm for Incremental Digital Display of Circular Arcs. Communications of the ACM 1987, 20, pp. 100106. [ Links ]

Van Aken J.R. An Efficient Ellipse Drawing Algorithm. CG&A, 4(9):24–35. 1984. [ Links ]

Roth G., Levine M.D. Geometric Primitive Extraction Using a Genetic Algorithm. IEEE Trans.Pattern Anal. Machine Intell, 16(9):901–905, 1994. [ Links ]

Cheng H.D., Guo Y., Zhang Y. A Novel Hough Transform Based on Eliminating Particle Swarm Optimization and its Applications. Pattern Recogn., 42(9):959–1969, 2009. [ Links ]

Ying–ping C., Pei J. Analysis of Particle Interaction in Particle Swarm Optimization. Theoretical Computer Science, 411(21):2101–2115, 2010. [ Links ]

Blum C. Ant Colony Optimization: Introduction and Recent Trends. Physics of Life Reviews, 2(4):353–373, 2005. [ Links ]

Vasan A., Raju K.S. Comparative Analysis of Simulated Annealing, Simulated Quenching and Genetic Algorithms for Optimal Reservoir Operation. Applied Soft Computing 9, 2009, pp. 274–281. [ Links ]