java基本概念解释:封装 (encapsulation) ,继承 (inherit) ,this用法,static ,final,super
标签： encapsulation inherit static final
上传时间： 2016-08-11
上传用户：gundamwzc
Fire and Fury。 This article is about the 2018 book. For other uses, see Fire and Fury (disambiguation). The title refers to a quote by Trump about the conflict with North Korea. The book became a New York Times number one bestseller.Fire and Fury: Inside the Trump White House is a 2018 book by Michael Wolff which details the behavior of U.S. President Donald Trump and the staff of his 2016 presidential campaign and White House. The book highlights descriptions of Trump's behavior, chaotic interactions among senior White House staff, and derogatory comments about the Trump family by former White House Chief StrategistSteve Bannon. Trump is depicted as being held in low regard by his White House staff, leading Wolff to state that "100% of the people around him" believe Trump is unfit for office.[1] Reviewers generally accepted Wolff's portrait of a dysfunctional Trump administration, but were skeptical of many of the book's most controversial claims.
上传时间： 2018-02-26
上传用户：Yoobaobao
This article is about the 2018 book. For other uses, see Fire and Fury (disambiguation). The title refers to a quote by Trump abot the conflict with North Korea. The book became a New York Times number one bestseller.Fire and Fury: Inside the Trump White House is a 2018 book by Michael Wolff which details the behavior of U.S. President Donald Trump and the staff of his 2016 presidential campaign and White House. The book highlights descriptions of Trump's behavior, chaotic interactions among senior White House staff, and derogatory comments about the Trump family by former White House Chief StrategistSteve Bannon. Trump is depicted as being held in low regard by his White House staff, leading Wolff to state that "100% of the people around him" believe Trump is unfit for office.[1] Reviewers generally accepted Wolff's portrait of a dysfunctional Trump administration, but were skeptical of many of the book's most controversial claims.
上传时间： 2018-02-26
上传用户：Yoobaobao
遗传算法已经成为组合优化问题的近似最优解的一把钥匙。它是一种模拟生物进化过程的计算模型，作为一种新的全局优化搜索算法，它以其简单、鲁棒性强、适应并行处理以及应用范围广等特点，奠定了作为21世纪关键智能计算的地位。 背包问题是一个典型的组合优化问题，在计算理论中属于NP-完全问题， 其计算复杂度为，传统上采用动态规划来求解。设w是经营活动 i 所需要的资源消耗，M是所能提供的资源总量，p是人们经营活动i得到的利润或收益，则背包问题就是在资源有限的条件下， 追求总的最大收益的资源有效分配问题。
上传时间： 2018-04-26
上传用户：jiazhe110125
#include <stdio.h> #include <stdlib.h> ///链式栈 typedef struct node { int data; struct node *next; }Node,*Linklist; Linklist Createlist() { Linklist p; Linklist h; int data1; scanf("%d",&data1); if(data1 != 0) { h = (Node *)malloc(sizeof(Node)); h->data = data1; h->next = NULL; } else if(data1 == 0) return NULL; scanf("%d",&data1); while(data1 != 0) { p = (Node *)malloc(sizeof(Node)); p -> data = data1; p -> next = h; h = p; scanf("%d",&data1); } return h; } void Outputlist(Node *head) { Linklist p; p = head; while(p != NULL ) { printf("%d ",p->data); p = p->next; } printf("\n"); } void Freelist(Node *head) { Node *p; Node *q = NULL; p = head; while(p != NULL) { q = p; p = p->next; free(q); } } int main() { Node *head; head = Createlist(); Outputlist(head); Freelist(head); return 0; } 2.顺序栈 [cpp] view plain copy #include <iostream> #include <stdio.h> #include <stdlib.h> ///顺序栈 #define MaxSize 100 using namespace std; typedef
上传时间： 2018-05-09
上传用户：123456..
function [alpha,N,U]=youxianchafen2(r1,r2,up,under,num,deta) %[alpha,N,U]=youxianchafen2(a,r1,r2,up,under,num,deta) %该函数用有限差分法求解有两种介质的正方形区域的二维拉普拉斯方程的数值解 %函数返回迭代因子、迭代次数以及迭代完成后所求区域内网格节点处的值 %a为正方形求解区域的边长 %r1,r2分别表示两种介质的电导率 %up,under分别为上下边界值 %num表示将区域每边的网格剖分个数 %deta为迭代过程中所允许的相对误差限 n=num+1; %每边节点数 U(n,n)=0; %节点处数值矩阵 N=0; %迭代次数初值 alpha=2/(1+sin(pi/num));%超松弛迭代因子 k=r1/r2; %两介质电导率之比 U(1,1:n)=up; %求解区域上边界第一类边界条件 U(n,1:n)=under; %求解区域下边界第一类边界条件 U(2:num,1)=0;U(2:num,n)=0; for i=2:num U(i,2:num)=up-(up-under)/num*(i-1);%采用线性赋值对上下边界之间的节点赋迭代初值 end G=1; while G>0 %迭代条件：不满足相对误差限要求的节点数目G不为零 Un=U; %完成第n次迭代后所有节点处的值 G=0; %每完成一次迭代将不满足相对误差限要求的节点数目归零 for j=1:n for i=2:num U1=U(i,j); %第n次迭代时网格节点处的值 if j==1 %第n+1次迭代左边界第二类边界条件 U(i,j)=1/4*(2*U(i,j+1)+U(i-1,j)+U(i+1,j)); end if (j>1)&&(j U2=1/4*(U(i,j+1)+ U(i-1,j)+ U(i,j-1)+ U(i+1,j)); U(i,j)=U1+alpha*(U2-U1); %引入超松弛迭代因子后的网格节点处的值 end if i==n+1-j %第n+1次迭代两介质分界面（与网格对角线重合）第二类边界条件 U(i,j)=1/4*(2/(1+k)*(U(i,j+1)+U(i+1,j))+2*k/(1+k)*(U(i-1,j)+U(i,j-1))); end if j==n %第n+1次迭代右边界第二类边界条件 U(i,n)=1/4*(2*U(i,j-1)+U(i-1,j)+U(i+1,j)); end end end N=N+1 %显示迭代次数 Un1=U; %完成第n+1次迭代后所有节点处的值 err=abs((Un1-Un)./Un1);%第n+1次迭代与第n次迭代所有节点值的相对误差 err(1,1:n)=0; %上边界节点相对误差置零 err(n,1:n)=0; %下边界节点相对误差置零 G=sum(sum(err>deta))%显示每次迭代后不满足相对误差限要求的节点数目G end
标签： 有限差分
上传时间： 2018-07-13
上传用户：Kemin
K-Means算法是最古老也是应用最广泛的聚类算法，它使用质心定义原型，质心是一组点的均值，通常该算法用于n维连续空间中的对象。 K-Means算法流程 step1：选择K个点作为初始质心 step2：repeat 将每个点指派到最近的质心，形成K个簇 重新计算每个簇的质心 until 质心不在变化 例如下图的样本集，初始选择是三个质心比较集中，但是迭代3次之后，质心趋于稳定，并将样本集分为3部分 我们对每一个步骤都进行分析 step1：选择K个点作为初始质心 这一步首先要知道K的值，也就是说K是手动设置的，而不是像EM算法那样自动聚类成n个簇 其次，如何选择初始质心 最简单的方式无异于，随机选取质心了，然后多次运行，取效果最好的那个结果。这个方法，简单但不见得有效，有很大的可能是得到局部最优。 另一种复杂的方式是，随机选取一个质心，然后计算离这个质心最远的样本点，对于每个后继质心都选取已经选取过的质心的最远点。使用这种方式，可以确保质心是随机的，并且是散开的。 step2：repeat 将每个点指派到最近的质心，形成K个簇 重新计算每个簇的质心 until 质心不在变化 如何定义最近的概念，对于欧式空间中的点，可以使用欧式空间，对于文档可以用余弦相似性等等。对于给定的数据，可能适应与多种合适的邻近性度量。
上传时间： 2018-11-27
上传用户：1159474180
1991年1月，在电子展上出现了NES版SimCity的原型。之后它再也没有出现 - 几个月后它出现在sfc上 - 但是视频游戏历史学家已经追踪了之前未被发现的版本，并将其上传到互联网上供所有人查看。
上传时间： 2019-04-11
上传用户：bzxgcs
In this paper we present a classifier called bi-density twin support vector machines (BDTWSVMs) for data classification. In the training stage, BDTWSVMs first compute the relative density degrees for all training points using the intra-class graph whose weights are determined by a local scaling heuristic strategy, then optimize a pair of nonparallel hyperplanes through two smaller sized support vector machine (SVM)-typed problems. In the prediction stage, BDTWSVMs assign to the class label depending on the kernel density degree-based distances from each test point to the two hyperplanes. BDTWSVMs not only inherit good properties from twin support vector machines (TWSVMs) but also give good description for data points. The experimental results on toy as well as publicly available datasets indicate that BDTWSVMs compare favorably with classical SVMs and TWSVMs in terms of generalization
标签： recognition Bi-density machines support pattern vector twin for
上传时间： 2019-06-09
上传用户：lyaiqing
RC5编码格式的遥控器解码、PCA9633器件控制代码示例、串口通信程序示例、IIC通信示例
标签： 9633 RC5 PCA IIC 编码 器件 代码 串口通信 控制 程序
上传时间： 2019-07-03
上传用户：zqy1818
