binary heap造句

例句与造句

1. Sifting up is done using the same process as in binary heaps.
2. Since binary heaps require \ Omega ( | A | ) time to merge, shadow merge remains efficient.
3. Binary trees labelled this way are used to implement binary search trees and binary heaps, and are used for efficient sorting.
4. The sift-down operation is slightly simpler than in binary heaps, because each node has either two children or zero.
5. Dijkstra's formulation of smoothsort does not use a binary heap, but rather a custom heap based on the Leonardo numbers.
6. It's difficult to find binary heap in a sentence. 用binary heap造句挺难的
7. The data structure resulting from this random choice is called a treap, due to its combination of binary search tree and binary heap features.
8. Leftist trees are advantageous because of their ability to merge quickly, compared to binary heaps which take ? ( " n " ).
9. In computer science, a "'binomial heap "'is a heap similar to a binary heap but also supports quick merging of two heaps.
10. Similarly, the priority queue may be a binary heap or any other logarithmic-time priority queue; more sophisticated priority queues such as a Fibonacci heap are not necessary.
11. It is also possible to merge two Fibonacci heaps in constant amortized time, improving on the logarithmic merge time of a binomial heap, and improving on binary heaps which cannot handle merges efficiently.
12. The advantage of this custom heap over a single binary heap is that if the input is already sorted, it can be constructed and deconstructed in time without moving any data, hence the better runtime.
13. As with binary heaps, weak heaps can support the typical operations of a priority queue data structure : insert, delete-min, delete, or decrease-key, in logarithmic time per operation.
14. Additionally, a binary heap can be implemented with a traditional binary tree data structure, but there is an issue with finding the adjacent element on the last level on the binary heap when adding an element.
15. Additionally, a binary heap can be implemented with a traditional binary tree data structure, but there is an issue with finding the adjacent element on the last level on the binary heap when adding an element.
16. 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 from a min-heap ( max-heap ).
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