References

  1. H.L. Liang, X.Y. Wu, M.L. Nong, F.S. Li, Effects of partial rootzone irrigation on yield and water use efficiency of sticky maize under the integrated management of water and fertilize. Agric. Res. Arid Areas., 5 (2012) 109–114.
  2. N. Wu, J.L. Liui, Existing problems and solutions of water and fertilizer integration in Ningxia. Ningxia J. Agric. Forestry Sci. Technol., 10 (2012) 124–126.
  3. T.N. Li , Y.T. Liu, Y. Li, Popularization effect and trend analysis of corn membrane drip irrigation technology in Heilongjiang Province. Modern Agric. Sci. Technol., 21 (2011) 105–107.
  4. S.M. Zai, F. Wu, J. Wen, Q.B Han, Effect of drip fertigation on soil salinity of cotton field in Northwest China. J. Hydr. Eng., 12 (2011) 1496–1502.
  5. D.L. Song, C.L. Lin, C.L. Zhang, E. Zeng, D.Q. Zheng, Integrated management of irrigation water and fertilizers for potato planting, Guangdong Agric. Sci., 15 (2011) 46–48.
  6. W.B. Du. Effects of drip fertigation on tomato in the solar greenhouse, J. Shanxi Agric. Sci., 1 (2009) 58–60.
  7. S.Z. Yu, Application of drip irrigation of integral control of water and fertilization for cucumber under protected cultivation in Shandong Province, J. Water Resour. Water Eng., 6 (2009) 173–176.
  8. J.J. Yuan Junjing, H.W. Li., Benefit evaluation of conservation tillage based on projection pursuit, Trans. Chinese Soc. Agric. Eng., 4 (2010) 175–176.
  9. Z.M. Feng, H.X. Zheng, B.Q. Liu., Comprehensive evaluation of agricultural water use efficiency based on genetic projection pursuit model, Trans. Chinese Soc. Agric. Eng., 3 (2005) 66–68.
  10. Q.X. Jiang, Q. Fu, Z.L. Wang, Comprehensive evaluation of regional land resources carrying capacity based on projection pursuit model optimized by particle swarm optimization, Trans. Chinese Soc. Agric. Eng., 11 (2011) 319–324.
  11. Simulating physics with computers, Int. J. Theor. Phys., 6(7) (1982) 467–488.
  12. P.W. Shor, Algorithms for quantum computation: Discrete logarithms and factoring. Proc of the 35th Annual Symp on Foundations of Computer Science, (1994), New York, USA, pp. 124–134.
  13. L.K. Grover, A fast quantum mechanical algorithm for database search. Proc of the 28th Annual ACM Symp on Theory of Computation, (1996), New York, USA, pp. 212–215.
  14. K.H. Han, J.H. Kim, Quantum-inspired evolutionary algorithm for a class of combinational optimization, IEEE Trans. Evol. Comp., 6 (2002) 580–593.
  15. X. Li, C.T. Cheng, Y. Zeng, Training of process neural networks based on improved quantum genetic algorithm, Control Decision, 3 (2009) 347–349.
  16. G.X. Zhang, N. Li, W.D. Jin, L.Z. Hu, A novel quantum genetic algorithm and its application, Acta Electron. Sinica., 3 (2004) 476–479.
  17. P.C. Li, K.P. Song, E.L. Yang, Phase encoded-based quantum ant optimization, Syst. Eng. Theory Practice, 8 (2011) 1565–1570.
  18. H.Y. Gao, J.L. Cao, Quantum-inspired bee colony optimization algorithm and its application for cognitive radio spectrum allocation, J. Central South University (Sci. Technol.), 43(12) (2012) 4743–4749.
  19. S.Y. Li, P.C. Li., Quantum Computation and Quantum Optimization Algorithms, Harbin Institute of Technology Press, Harbin 2009.
  20. M.X. Sun, X.P. Chen, An immune algorithm based on the vector distance applied to function optimization, J. Suzhou Univ.(Eng. Sci. Ed., 3 (2010) 56–57.
  21. Y.B. Duan, W.J. Ren, F.C. Huo, A kind of new immune genetic algorithm and its application, Control Decision., 10 (2005) 1185–1186.
  22. H. Ge, Z.Y. Mao, Realization of immune algorithm, Comp. Eng., 5 (2003) 62–63.
  23. S.H. Xiao, H.Y. Lu, A.D. Fan, H. Song, Applied Research of Simulated Annealing algorithm on solving combinatoria1 optimization problems, J. Sichuan Univ. Sci. Eng. (Nat. Sci. Ed.)., 1 (2010) 116–118.
  24. H.D. Zhu, Y. Zhong., A kind of renewed simulated annealing algorithm, Comp. Technol. Develop., 6 (2009) 32–35.