Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
1 makes sense for somewhere you haven't been before. 2 could be interesting, but it's a bit superfluous if not required. 3 is the most important and essential. Some teachers don't want presenters to look at the board/read their slides word for word when they present, so it might be a good idea to have note cards instead.
Hope this helps!
Read and follow procedures as outlined in the operator's manual. By being familiar with the operating features of a tractor, the operator will develop confidence when the tractor is driven under adverse conditions. Learn the location and purpose of all of the guages and controls as well as other indicators. Knowing where the controls are by memory can allow you to react more quickly in an emergency situation. There have been accident situations where individuals have become entangled in machinery or the power takeoff shaft and rescuers or family did not know how to disengage the equipment. Family members should be showed how to shut down equipment or disengage the PTO in case of emergency.
Study the various decals on your equipment. They may point out DANGER, WARNING and CAUTION for various points on the tractor. Have an experienced tractor operator with you as you review the various decals and ask questions!
What is "listing 9.1"?
Stop copying and pasting, or provide us with the resources to answer your question.
Answer:
intranet
Explanation:
An intranet is a private network that you can't access outside the physical boundary of an organization
