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拉格朗日插值法是工程中常用的函数近似重构技术,其有效性与采样点的位置选择密切相关。细菌觅食优化算法(BFOA)则是一种新兴的模拟大肠杆菌觅食行为的群体智能算法,目前尚未得到广泛的应用。提出利用细菌觅食优化算法进行拉格朗日插值点的优化求解,结果优于传统方法。本研究验证了细菌觅食优化算法的有效性,同时为拉格朗日插值点的最优配置提供了新的解决思路。
Lagrange interpolation is a commonly used function approximation reconstruction technique in engineering. Its effectiveness is closely related to the choice of sampling points. Bacterial foraging optimization algorithm (BFOA) is a new swarm intelligence algorithm that simulates the foraging behavior of E. coli and has not been widely used. Proposed optimization of bacterial foraging optimization Lagrange interpolation points, the result is better than the traditional method. This study validates the effectiveness of the bacterial foraging optimization algorithm and provides a new solution to the optimal placement of Lagrange interpolation points.