Citations in impact factor journals
Investigating Smart Sampling as a population initialization method for Differential Evolution in continuous problems Information Sciences |
Modeling and Optimization of Acid Blue 193 Removal by UV and
Peroxydisulfate Process Journal of Environmental Engineering Vol. 144, Issue 8, 06018003, 2018 |
Citation to this article as recorded by
Pavan, K.K., V.S. Srinivas, A. SriKrishna and B.E. Reddy, 2012. Automatic tissue segmentation in medical images using differential evolution. J. Applied Sci., 12: 587-592. CrossRefDirect Link |
Wang, Y.H., X.K. Wang and H.F. Teng, 2012. Opposition-based cooperative coevolutionary differential evolution algorithm with gaussian mutation for simplified satellite module optimization. Inform. Technol. J., 11: 67-75. CrossRefDirect Link |
Citation to this article as recorded by
An Investigation of Mechanical Properties of Polyurethane
Nanocomposites with Various Silicas: Experimental Study and Modeling of Finite
Deformation Response Silicon |
Economic load dispatch problem: quasi-oppositional self-learning
TLBO algorithm Energy Systems Vol. 9, Issue 2, 415, 2018 |
Triple-band Inverted-F Antenna Using QR-OBL TLBO Algorithm for RF Energy Harvesting Applications 2020 9th International Conference on Modern Circuits and Systems Technologies (MOCAST) |
Self-adaptive uniform differential evolution for optimizing the
initial integral point of the Earth–Moon low-energy transfer Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering Vol. 225, Issue 11, 1263, 2011 |
Opposition-based Cooperative Coevolutionary Differential Evolution Algorithm With Gaussian Mutation for Simplified Satellite Module Optimization Information Technology Journal Vol. 11, Issue 1, 67, 2012 |
A Novel Differential Evolution with Uniform Design for Continuous Global Optimization Journal of Computers Vol. 7, Issue 1, , 2012 |
How to cite this article
Lei Peng and Yuanzhen Wang, 2010. Differential Evolution using Uniform-Quasi-Opposition for Initializing the Population. Information Technology Journal, 9: 1629-1634.
DOI: 10.3923/itj.2010.1629.1634
URL: https://scialert.net/abstract/?doi=itj.2010.1629.1634
DOI: 10.3923/itj.2010.1629.1634
URL: https://scialert.net/abstract/?doi=itj.2010.1629.1634