Location:
Search - max heap
Search list
Description: //Demo of the heap ADT (maxheap). For documentation
// see the lecture slides.
Platform: |
Size: 1024 |
Author: zhang wei |
Hits:
Description: 大小堆实验源码,用于建立，查看，删除，插入等等操作的实现。-min-max heap experiment
Platform: |
Size: 358400 |
Author: needtobestrong |
Hits:
Description: 1. 此程式執行將從路徑讀取一個文字檔 ( 路徑：C:INPUT.TXT )
2. 執行結束會產生一個排序後的文字檔 ( 路徑：C:OUTPUT.TXT )
3. 給定的初始盤面一定有解
本程式採用的演算法策略為Best-first search with branch-and-bound algorithm
1. 使用Max heap 實作Priority queue
2. 使用bound function 估計目前盤面走至答案最少需要幾步
第一部分
所謂 heap property (或稱 heap condition) 是指每個 node 內的資料比它左右兩側 child nodes 內的資料都小 (但左右兩 child nodes 之間並無一定的關係)。
雖說 heap 在觀念上是一棵 complete binary tree, 實際上是存在一個陣列當中 root 存在 A[1], 接下來將 A[2] 與 A[3] 由左到右依序補滿第二層, 再將 A[4], A[5], A[6], A[7] 由左到右依序補滿第三層…。-1. This program is running from the path to read a text file (path: C: INPUT.TXT)
2. Implementation of the end will produce a sorted text file (path: C: OUTPUT.TXT)
3. Given the initial disk of at least one solution
The program uses the algorithm strategy Best-first search with branch-and-bound algorithm
1. Using the Max heap implement Priority queue
2. Bound function is estimated using the disk at least a few steps away to answer
The first part
The so-called heap property (or called heap condition) refers to the information within each node than its left and right child nodes of the information is small (about two child nodes, but there is no necessary relationship between).
Although the concept of heap is a complete binary tree, in fact there exist root among an array A [1], then the A [2] and A [3] from left to right order of fill over the second layer, then A [4], A [5], A [6], A [7] from left to right order of filling up the third tier ....
Platform: |
Size: 2048 |
Author: zelda |
Hits:
Description: 利用heap实现三叉树的组建，插入，排序。
分析推导 算法的时间复杂度。 - create a max heap class that is based on a complete ternary tree. As with a complete binary tree max heap, the
largest value is at the root and the root is at location 1 in the vector holding the heap. Location 0 is
unused.1）insert2）delete3）build
Platform: |
Size: 6144 |
Author: chengxiaoxin |
Hits:
Description: a heap class + program wriitten in c++. it implements a max heap
Platform: |
Size: 2048 |
Author: miss24 |
Hits:
Description: the c source code of max heap
Platform: |
Size: 1024 |
Author: Peter |
Hits:
Description: max heap sorce code and it is good
Platform: |
Size: 1024 |
Author: king |
Hits:
Description: The heapsort algorithm can be divided into two parts.
In the first step, a heap is built out of the data.
In the second step, a sorted array is created by repeatedly removing the largest element from the heap, and inserting it into the array. The heap is reconstructed after each removal. Once all objects have been removed from the heap, we have a sorted array. The direction of the sorted elements can be varied by choosing a min-heap or max-heap in step one.
Heapsort can be performed in place. The array can be split into two parts, the sorted array and the heap.The heap s invariant is preserved after each extraction, so the only cost is that of extraction.
Platform: |
Size: 6144 |
Author: subodh |
Hits:
Description: 使用循环队列创建最小和最大优先队列，并使用堆排序方法去排序。-Using the circular queue to create the min and max priority queue, and using heap sort method to sort the queue.
Platform: |
Size: 211968 |
Author: kid |
Hits:
Description: 利用C++编程语言解决数据结构中的最大堆问题。-Using C++ programing language to solve the problems of Max-heap in data structure.
Platform: |
Size: 4077568 |
Author: 祝山峰 |
Hits:
Description: Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.-Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.
Platform: |
Size: 1024 |
Author: Carabian Ovidiu |
Hits: