Adaptive neural network model identification of uncertainty systems can be described as optimization of a non - stationary function 不确定系统的自适应神经网络模型辨识的实质是一个时变函数优化问题，克隆选择算法适应性强，适合用于求解此类优化问题。
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Results showed csa had strong ability of function optimization and maintaining diversity . it was one of effective algorithms for multi - modal functions and non - stationary functions optimization 研究结果表明，该算法优化能力和保持模式多样性的能力较强，能够获得较好的多模态函数和时变函数优化效果。
