Title of article :
Ant colony optimization for nonlinear AVO inversion of network traffic allocation optimization
Author/Authors :
Shi-chang، نويسنده , , Li and Qing-sheng، نويسنده , , Zhu Chao-Zhe، نويسنده , , Yan and Hao-lan، نويسنده , , Yang، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
5
From page :
8343
To page :
8347
Abstract :
Most local optimization algorithms are hard to search the global minimum. In this paper, we implemented and tested an AVO inversion scheme based on ACO algorithms. The ant colony optimization (ACO) algorithms are inspired by the behavior of ants to find solutions to combinatorial optimization problem. Inversion results of synthetic data and real model demonstrate that ACO algorithms applied in nonlinear AVO inversion should be considered well not only in terms of accuracy but also in terms of computation effort. Meanwhile it can provide a new approach to solve the nonlinear problems of network traffic allocation optimization.
Keywords :
AVO inversion , Global minimum , network traffic , Allocation optimization , ACO algorithms
Journal title :
Expert Systems with Applications
Serial Year :
2010
Journal title :
Expert Systems with Applications
Record number :
2348556
Link To Document :
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