針對二分查找算法中的mid定義,
我們可以優化些,二分查找中,mid = (left + right)/2
我們可以寫成mid = left + (right - left)/2
針對除數2,我們可以有個優化,
用(targe - arr[left])/(arr[right] - arr[left])來替代2,這樣,
每次取mid時會更加接近targe值
package Search;
public class InsertValueSearch {
//差值查找(只要是mid定義變了,變成了mid = left + (targe - arr[left])/(arr[right]-arr[left])*(right - left))
//該方法能更加快速的接近和自己最近的元素,查找輪次更少
public static void main(String[] args) {
// TODO Auto-generated method stub
InsertValueSearch insertValueSearch = new InsertValueSearch();
int[] arr = new int[1000];
for(int i = 0;i<arr.length; i++) {
arr[i] = i+1;
}
int index = insertValueSearch.binarySearch(arr, 0, arr.length-1, 900);
System.out.println(index);
index = insertValueSearch.insertValueSearch(arr, 0, arr.length-1, 900);
System.out.println(index);
}
public int insertValueSearch(int[] arr,int left,int right,int targe) {
System.out.println("差值查找~");
if(left > right || targe < arr[left] || targe > arr[right]) {
return -1;
}
int mid = left + (targe - arr[left])* (right - left)/(arr[right] - arr[left]) ;
System.out.println("mid:"+mid);
if(targe > arr[mid]) {
return insertValueSearch(arr, mid+1, right, targe);
}else if(targe < arr[mid]) {
return insertValueSearch(arr, left, mid-1, targe);
}else {
return mid;
}
}
public int binarySearch( int[] arr, int left, int right,int targe) {
System.out.println("二分查找~");
if(left > right) {
return -1;
}
int mid = (left + right)/2;
System.out.println("mid:"+mid);
if(targe > arr[mid]) {//mid--right
return binarySearch( arr, mid+1, right,targe);
}else if(targe < arr[mid]) {//left --- mid
return binarySearch( arr, left, mid - 1,targe);
}else {
return mid;
}
}
}
差值查找算法在數據量大,數據有序,且整體均勻的時候,速度比二分查找算法快。