java基本概念解釋:封裝 (encapsulation) ,繼承 (inherit) ,this用法,static ,final,super
標簽： encapsulation inherit static final
上傳時間： 2016-08-11
上傳用戶：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.
上傳時間： 2018-02-26
上傳用戶：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.
上傳時間： 2018-02-26
上傳用戶：Yoobaobao
遺傳算法已經成為組合優化問題的近似最優解的一把鑰匙。它是一種模擬生物進化過程的計算模型，作為一種新的全局優化搜索算法，它以其簡單、魯棒性強、適應并行處理以及應用范圍廣等特點，奠定了作為21世紀關鍵智能計算的地位。 背包問題是一個典型的組合優化問題，在計算理論中屬于NP-完全問題， 其計算復雜度為，傳統上采用動態規劃來求解。設w是經營活動 i 所需要的資源消耗，M是所能提供的資源總量，p是人們經營活動i得到的利潤或收益，則背包問題就是在資源有限的條件下， 追求總的最大收益的資源有效分配問題。
上傳時間： 2018-04-26
上傳用戶：jiazhe110125
#include <stdio.h> #include <stdlib.h> ///鏈式棧 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.順序棧 [cpp] view plain copy #include <iostream> #include <stdio.h> #include <stdlib.h> ///順序棧 #define MaxSize 100 using namespace std; typedef
上傳時間： 2018-05-09
上傳用戶：123456..
function [alpha,N,U]=youxianchafen2(r1,r2,up,under,num,deta) %[alpha,N,U]=youxianchafen2(a,r1,r2,up,under,num,deta) %該函數用有限差分法求解有兩種介質的正方形區域的二維拉普拉斯方程的數值解 %函數返回迭代因子、迭代次數以及迭代完成后所求區域內網格節點處的值 %a為正方形求解區域的邊長 %r1,r2分別表示兩種介質的電導率 %up,under分別為上下邊界值 %num表示將區域每邊的網格剖分個數 %deta為迭代過程中所允許的相對誤差限 n=num+1; %每邊節點數 U(n,n)=0; %節點處數值矩陣 N=0; %迭代次數初值 alpha=2/(1+sin(pi/num));%超松弛迭代因子 k=r1/r2; %兩介質電導率之比 U(1,1:n)=up; %求解區域上邊界第一類邊界條件 U(n,1:n)=under; %求解區域下邊界第一類邊界條件 U(2:num,1)=0;U(2:num,n)=0; for i=2:num U(i,2:num)=up-(up-under)/num*(i-1);%采用線性賦值對上下邊界之間的節點賦迭代初值 end G=1; while G>0 %迭代條件：不滿足相對誤差限要求的節點數目G不為零 Un=U; %完成第n次迭代后所有節點處的值 G=0; %每完成一次迭代將不滿足相對誤差限要求的節點數目歸零 for j=1:n for i=2:num U1=U(i,j); %第n次迭代時網格節點處的值 if j==1 %第n+1次迭代左邊界第二類邊界條件 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網格節點處的值 end if i==n+1-j %第n+1次迭代兩介質分界面（與網格對角線重合）第二類邊界條件 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次迭代右邊界第二類邊界條件 U(i,n)=1/4*(2*U(i,j-1)+U(i-1,j)+U(i+1,j)); end end end N=N+1 %顯示迭代次數 Un1=U; %完成第n+1次迭代后所有節點處的值 err=abs((Un1-Un)./Un1);%第n+1次迭代與第n次迭代所有節點值的相對誤差 err(1,1:n)=0; %上邊界節點相對誤差置零 err(n,1:n)=0; %下邊界節點相對誤差置零 G=sum(sum(err>deta))%顯示每次迭代后不滿足相對誤差限要求的節點數目G end
標簽： 有限差分
上傳時間： 2018-07-13
上傳用戶：Kemin
K-Means算法是最古老也是應用最廣泛的聚類算法，它使用質心定義原型，質心是一組點的均值，通常該算法用于n維連續空間中的對象。 K-Means算法流程 step1：選擇K個點作為初始質心 step2：repeat 將每個點指派到最近的質心，形成K個簇 重新計算每個簇的質心 until 質心不在變化 例如下圖的樣本集，初始選擇是三個質心比較集中，但是迭代3次之后，質心趨于穩定，并將樣本集分為3部分 我們對每一個步驟都進行分析 step1：選擇K個點作為初始質心 這一步首先要知道K的值，也就是說K是手動設置的，而不是像EM算法那樣自動聚類成n個簇 其次，如何選擇初始質心 最簡單的方式無異于，隨機選取質心了，然后多次運行，取效果最好的那個結果。這個方法，簡單但不見得有效，有很大的可能是得到局部最優。 另一種復雜的方式是，隨機選取一個質心，然后計算離這個質心最遠的樣本點，對于每個后繼質心都選取已經選取過的質心的最遠點。使用這種方式，可以確保質心是隨機的，并且是散開的。 step2：repeat 將每個點指派到最近的質心，形成K個簇 重新計算每個簇的質心 until 質心不在變化 如何定義最近的概念，對于歐式空間中的點，可以使用歐式空間，對于文檔可以用余弦相似性等等。對于給定的數據，可能適應與多種合適的鄰近性度量。
上傳時間： 2018-11-27
上傳用戶：1159474180
1991年1月，在電子展上出現了NES版SimCity的原型。之后它再也沒有出現 - 幾個月后它出現在sfc上 - 但是視頻游戲歷史學家已經追蹤了之前未被發現的版本，并將其上傳到互聯網上供所有人查看。
上傳時間： 2019-04-11
上傳用戶：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
標簽： recognition Bi-density machines support pattern vector twin for
上傳時間： 2019-06-09
上傳用戶：lyaiqing
RC5編碼格式的遙控器解碼、PCA9633器件控制代碼示例、串口通信程序示例、IIC通信示例
標簽： 9633 RC5 PCA IIC 編碼 器件 代碼 串口通信 控制 程序
上傳時間： 2019-07-03
上傳用戶：zqy1818
