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化学问题中经常遇到需要用近似方法求解复杂化学方程(包括非线性方程,超越方程等)根的问题。传统的方法有图解法,牛顿迭代法等,但不是所有问题都可解决,因为用传统方法可能受初值选取的影响也可能求解精度不高。因此改进进化策略,把复杂化学方程求根转化成函数优化问题,并充分利用改进进化策略具有自适应性和鲁棒性的特点,从随机产生的初始可行解出发,经过优化选择、重组、突变等操作,迭代逐渐逼近最优解,同时体现并行算法的特点。最后,本文通过仿真实例表明新算法具有收敛快、求解精度高等优点。
Chemical problems often encounter the need to approximate the solution of complex chemical equations (including nonlinear equations, transcendental equations, etc.) root problems. The traditional methods are graphical method, Newton iteration method, but not all problems can be solved, because the traditional method may be affected by the selection of the initial value may not be accurate solution. Therefore, the evolutionary strategy is improved. The complex chemical equation is transformed into a function optimization problem by roots. The evolutionary strategy is fully adaptive and robust. From the initial feasible solution, the optimal selection, recombination and mutation And other operations, iterative gradually approaching the optimal solution, while reflecting the characteristics of parallel algorithms. Finally, the simulation example shows that the new algorithm has the advantages of fast convergence and high solution accuracy.