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<div id="pf1" class="pf w0 h0" data-page-no="1"><div class="pc pc1 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="https://static.pudn.com/prod/directory_preview_static/627050b57b370112142f5990/bg1.jpg"><div class="c x0 y1 w2 h2"><div class="t m0 x1 h3 y2 ff1 fs0 fc0 sc0 ls0 ws0">/****************************************************************</div><div class="t m0 x1 h3 y3 ff1 fs0 fc0 sc0 ls0 ws0">******** </div><div class="t m0 x1 h4 y4 ff1 fs0 fc0 sc0 ls0 ws0">* <span class="ff2">用改进的欧拉方法求解初值问题,其中一阶微分方程未<span class="_ _0"> </span></span>y'=f(x,y) </div><div class="t m0 x1 h4 y5 ff1 fs0 fc0 sc0 ls0 ws0">* <span class="ff2">初始条件为<span class="_ _0"> </span></span>x=x[0]<span class="ff2">时</span>,y<span class="ff2">=</span>y[0]. </div><div class="t m0 x1 h4 y6 ff1 fs0 fc0 sc0 ls0 ws0">* <span class="ff2">输入</span>: f--<span class="ff2">函数<span class="_ _0"> </span></span>f(x,y)<span class="ff2">的指针</span> </div><div class="t m0 x1 h4 y7 ff1 fs0 fc0 sc0 ls0 ws0">* x--<span class="ff2">自变量离散值数组</span>(<span class="ff2">其中<span class="_ _0"> </span></span>x[0]<span class="ff2">为初始条件</span>) </div><div class="t m0 x1 h4 y8 ff1 fs0 fc0 sc0 ls0 ws0">* y--<span class="ff2">对应于自变量离散值的函数值数组</span>(<span class="ff2">其中<span class="_ _0"> </span></span>y[0]<span class="ff2">为初始条件</span>) </div><div class="t m0 x1 h4 y9 ff1 fs0 fc0 sc0 ls0 ws0">* h--<span class="ff2">计算步长</span> </div><div class="t m0 x1 h4 ya ff1 fs0 fc0 sc0 ls0 ws0">* n--<span class="ff2">步数</span> </div><div class="t m0 x1 h4 yb ff1 fs0 fc0 sc0 ls0 ws0">* <span class="ff2">输出</span>: x<span class="_ _0"> </span><span class="ff2">为说求解的自变量离散值数组</span> </div><div class="t m0 x1 h4 yc ff1 fs0 fc0 sc0 ls0 ws0">* y<span class="_ _0"> </span><span class="ff2">为所求解对应于自变量离散值的函数值数组</span> </div><div class="t m0 x1 h3 yd ff1 fs0 fc0 sc0 ls0 ws0">*****************************************************************</div><div class="t m0 x1 h3 ye ff1 fs0 fc0 sc0 ls0 ws0">*******/ </div><div class="t m0 x1 h3 yf ff1 fs0 fc0 sc0 ls0 ws0">double proved_euler(double(*f)(double,double),double x[], </div><div class="t m0 x1 h3 y10 ff1 fs0 fc0 sc0 ls0 ws0">double y[],double h,int n) </div><div class="t m0 x1 h3 y11 ff1 fs0 fc0 sc0 ls0 ws0">{ </div><div class="t m0 x1 h3 y12 ff1 fs0 fc0 sc0 ls0 ws0">int i; </div><div class="t m0 x1 h3 y13 ff1 fs0 fc0 sc0 ls0 ws0">double xs,ys,yp; </div><div class="t m0 x1 h3 y14 ff1 fs0 fc0 sc0 ls0 ws0">for(i=0;i<n;i++) </div><div class="t m0 x1 h3 y15 ff1 fs0 fc0 sc0 ls0 ws0">{ </div><div class="t m0 x1 h3 y16 ff1 fs0 fc0 sc0 ls0 ws0">ys=y<span class="ff3">; </span></div><div class="t m0 x1 h3 y17 ff3 fs0 fc0 sc0 ls0 ws0">xs=x; </div><div class="t m0 x1 h3 y18 ff3 fs0 fc0 sc0 ls0 ws0">y[i+1]=y; </div><div class="t m0 x1 h3 y19 ff3 fs0 fc0 sc0 ls0 ws0">yp=(*f)(xs,ys); //k1 </div><div class="t m0 x1 h3 y1a ff3 fs0 fc0 sc0 ls0 ws0">y[i+1]+=yp*h/2.0; </div><div class="t m0 x1 h3 y1b ff3 fs0 fc0 sc0 ls0 ws0">ys+=h*yp; </div><div class="t m0 x1 h3 y1c ff3 fs0 fc0 sc0 ls0 ws0">xs+=h; </div><div class="t m0 x1 h3 y1d ff3 fs0 fc0 sc0 ls0 ws0">yp=(*f)(xs,ys); //k2 </div><div class="t m0 x1 h3 y1e ff3 fs0 fc0 sc0 ls0 ws0">y[i+1]+=yp*h/2.0; </div><div class="t m0 x1 h3 y1f ff3 fs0 fc0 sc0 ls0 ws0">x[i+1]=xs; </div><div class="t m0 x1 h3 y20 ff3 fs0 fc0 sc0 ls0 ws0">} </div><div class="t m0 x1 h3 y21 ff3 fs0 fc0 sc0 ls0 ws0">return(0); </div><div class="t m0 x1 h3 y22 ff3 fs0 fc0 sc0 ls0 ws0">}</div></div></div><div class="pi" data-data='{"ctm":[1.611850,0.000000,0.000000,1.611850,0.000000,0.000000]}'></div></div>
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