期刊文献+

数字对讲机中继站分配的最优化 被引量:1

The Optimization of Repeater Distribution for Digital Interphone
下载PDF
导出
摘要 本文针对模拟对讲机向数字对讲机过渡的过程中中继站的分配问题,基于蜂窝覆盖原理,提出利用移动伪区域法和免疫算法对不同地形中中继站分配最优化的方法。首先根据规划区域面积以及数字和模拟对讲机用户数目来估算所需中继站的数目并计算中继站有效作用距离,之后利用移动伪区域法和免疫算法分别对平坦地形区域和复杂地形区域进行仿真。仿真结果证明该方法的有效性和可行性。 Based on the allocation problem existing in the transition from analog interphone to digital interphone and the cellular covering theory,this passage aims at proposing the optimized version of repeater in different terrain,using the Moving Pseudo-area method and Immune Algorithm.At first we should estimate the number of repeater and its effective distance according to the planning area and the number of the users.And then we would use the Moving Pseudo-area methods and Immune Algorithm to emulate the subdued topography and complex topography.The emulation result will prove the effectiveness and feasibility of the version.
出处 《价值工程》 2011年第29期143-144,共2页 Value Engineering
关键词 数字对讲机 中继站分配 最优化 移动伪区域法 免疫算法 digital interphone repeater distribution optimization Moving Pseudo-area methods Immune Algorithm
  • 相关文献

参考文献2

二级参考文献8

  • 1Fonseca C M, Fleming P J. An overview of evolutionary algorithms in multiobjective optimization[J]. Evolutionary Computation, 1995,3(1):1-16.
  • 2Jern N K. The immune system[J]. Scientific American, 1973,229(1):52-60.
  • 3Echart Zitzler, Kzlyanmoy Deb, Lothar thiele[J]. Comparison of multiobjective evolutionary algorithms: empirical results.Evolutionary Computation, 2000, 8(2):173-195.
  • 4Zitzler E, Thiele L. An evolutionary algorithm for multiobjective optimization: the strength Pareto approach [R]. Technical Report TIK43, Computer Engineering and Communication Networks Lab, Swiss Federal Institute of Technology, Gloriastrasse 35, 8092, Zurich, Switzerland, May 1998.
  • 5Horn J, Nafpliotis N. Multiobjective optimization using the riched pareto genetic algorithm [R]. Technical Report. llliGAL Report 93005, University of Illinois at Urbana Champaign, Urbana, Illinois, USA, 1993.
  • 6Srinivas N, Kalyanmoy D. Multiobjective optimization using nondominated sorting in genetic algorithms [J]. Evolutionary Computation, 1994,2(3):221-248.
  • 7Fonseca C M, Fleming P J. Genetic algorithm for multiobjective optimization: formulation, discussion and generation[C]. Proceedings of the Fifth International Conference on Genetic Algorithms, 1993, 416-42.
  • 8谢涛,陈火旺.多目标优化与决策问题的演化算法[J].中国工程科学,2002,4(2):59-68. 被引量:59

共引文献10

同被引文献7

引证文献1

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部