Question #6 Use the following graph to find the path using (A is the start symbol and J is the Goal) a) A* search b) Best First Search c) Breadth Search d) Is the heuristic function admissible? 10 (A 3 6 8 8 B 2 5 3 8 5 3 5 5 1 3 JO 7 3

Question #6 Use the following graph to find the path using (A is the start symbol and J is the Goal) a) A* search b) Best First Search c) Breadth Search d) Is the heuristic function admissible? 10 (A 3 6 8 8 B 2 5 3 8 5 3 5 5 1 3 JO 7 3

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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] ] hav_hak Write a function "hav_hak(Ist)" that takes in a list of non-increasing integers as its input, and then determines whether or not this is the degree sequence of a graph. After compiling the above cell, you should be able to compile the following cell and obtain the desired outputs. print (hav_hak( [3,3,3,3,3]), hav_hak( [3,3,2,2,2,2])) This should return False True + Code + Markdown Python Python
7. Required information NOTE: This is a multi-part question. Once an answer is submitted, you will be unable to return to this part. Find the number of paths between cand d in the following graph of length b There are e C paths of length 7.
] ] has_perfect You are to write a function has "perfect (graph)" that takes in a BIPARTITE graph as its input, and then determintes whether or not the graph has a perfect matching. In other words, it will return the Boolean value True if it has one, and False if it does not. After compiling the above cell, you should be able to compile the following cell and obtain the desired outputs. print (has perfect({"A" : ["B", "C"], "B" : ["A", "D"], "C" : ["A", "D"], "D" : ["B", "C"]}), has perfect ( {"A" : ["B"], "B" : ["A", "D", "E"], "C" : ["E"], "D":["B"], "E": ["B","C","F"], "F":["E"]})) This should return True False Python Python
Data structure/ C language / Graph / Dijkstra’s algorithm implement a solution of a very common issue: howto get from one town to another using the shortest route.* design a solution that will let you find the shortest paths betweentwo input points in a graph, representing cities and towns, using Dijkstra’salgorithm. Your program should allow the user to enter the input filecontaining information of roads connecting cities/towns. The programshould then construct a graph based on the information provided from thefile. The user should then be able to enter pairs of cities/towns and thealgorithm should compute the shortest path between the two cities/townsentered.Attached a file containing a list of cities/towns with the following data:Field 1: Vertex ID of the 1st end of the segmentField 2: Vertex ID of the 2nd of the segmentField 3: Name of the townField 4: Distance in KilometerPlease note that all roads are two-ways. Meaning, a record may representboth the roads from feild1 to field2…
] ] is_bipartite In the cell below, you are to write a function "is_bipartite (graph)" that takes in a graph as its input, and then determines whether or not the graph is bipartite. In other words, it returns True if it is, and False if it is not. After compiling the above cell, you should be able to compile the following cell and obtain the desired outputs. print (is_bipartite({"A" : ["B", "C"], "B" : ["A"], "C" : ["A"]}), is_bipartite({"A" : ["B", "C"], "B" : ["A", "C"], "C" : ["A", "B"]})) This should return True False Python Python
Application: Apply Algorithm (Q5 – Q7) The following questions ask you to manually apply an algorithm introduced in the lecture and demonstrate your understanding by describing intermediate states of the computation. Question 5 (Sorting) Write down the list content at the end of each iteration of the main loop (ie. end of each pass) of Insertion Sort for the following list: [14,12,7,4,18,9] Use one line for each pass. Question 6 (Graph Traversal) Apply Depth First Search (DFS) to traverse the following graph. Start your traversal from vertex 0, and write down the order in which vertices will be visited during the traversal. (image for this question also attached) Question 7 (Gaussian elimination) (image for this question also attached) Apply forward elimination to this system of linear equations to put it into the upper triangular form. ⎛⎝⎜⎜1 1 2225−12−1⎞⎠⎟⎟⎛⎝⎜⎜? ? ?⎞⎠⎟⎟=⎛⎝⎜⎜6 3 13⎞⎠⎟⎟(12−1 122 25−1)(� � �)=(6 3 13) Write each row operation you use to solve the problem. Find…
C++, void traverseWithDijkstra(string start); ➔Use Dijkstra's algorithm to compute the single source shortest path in the graph from the start city to all other nodes in its component. ➔You don’t print anything in this function. Storing the distance associated with every node relative to the start node is enough. .hpp #ifndef GRAPH_H #define GRAPH_H #include<vector> #include<iostream> using namespace std; struct vertex; struct adjVertex{ vertex *v; int weight; }; struct vertex{ vertex() { this->visited = false; this->distance = 0; this->pred = NULL; } string name; bool visited; int distance; vertex *pred; vector<adjVertex> adj; }; class Graph { public: void createEdge(string v1, string v2, int num); void insertVertex(string name); void displayEdges(); void depthFirstTraversal(string sourceVertex); void traverseWithDijkstra(string sourceVertex); void minDistPath(string start, string end); private: vector<vertex*> vertices; };
Problem Statement: Write a program which should create a weighted graph of the values entered by the user and then write functions that perform the following: 1. Depth first search of source and destination vertex 2. Breadth first search of source and destination vertex 3. Shortest path search of source and all destination vertices (Dijkstra's algorithm) 4. Shortest path search of source and destination vertex (Dijkstra's algorithm) The program should present a menu of the options and should run until the user opts to quit.
c) An expression of A + B^3 – C/D is obtained using a rooted tree. i. Draw a rooted tree with the height of 2 to represent the postorder traversal. ii. Justify whether the rooted tree in 3-c(i) is balanced or not. iii. From tree in c(i), get the mathematical expression using the inorder traversal. d) Figure 3 represents a network of paths in a park. The number on each edge represents the length of the path in meters. The cost per meter is RM120. To gain as much profit, the contractor asked one of his staff to find the minimum network needed using Kruskal's algorithm. G 21 16 17 21 F 11 23 E 11 7 15 18 В 11 20 A Figure 3 i. Explain why the staff's work which is highlighted in red is incorrect. ii. Help the staff to find the correct minimum network using Kruskal's algorithm and states its length and total cost. iii. Is there any possibiliy, more than one distint MST obtained for the Figure 3?. If yes, justify your answer and show the network.
Botathon Question 9: Code the following problem statement using python: You are given a tree that is buit in a following way: initially there is single vertex 1. All the other vertices are added one by one, from vertex 2 to vertex N, by connecting it to one of those that have been added before. You are to find the diameter of the tree after adding each vertex. Let the distance between vertexu and v be the minimal number of edges e t f you have to pass to get from u to v, then diameter is the maximum distance between any two pairs (u,v) that have already been added to the tree. Input: 2 Output: 1 2 8CSA 2017
Python Graph Algorithms: Minimum Spanning Trees Note: There are helper functions (see 'required' below), and some of them (like Kruskal's Algorithm, WeightedQuickUnion, and such) can help answering this problem. Problem: Suppose you are an engineer working on designing a road network for a new town. The town has many residential areas and commercial centers that need to be connected efficiently. You decided to represent the town as a connected, undirected graph where each vertex represents a location, and each edge represents a road connecting two locations. The weight of each edge represents the distance between the two locations. To ensure the road network is efficient, you need to find the minimum spanning tree of the graph. However, due to budget constraints, you can only construct roads with a maximum distance limit. You need to determine for how many pairs of locations, the minimum spanning tree of the graph remains the same when the maximum distance limit of a road is increased…
Exercise # 2: Map search For the location map search example explained in the Greedy best first search and A* algorithm, change the search algorithm to follow the uniform cost algorithm (UCS). Run the new code and compare the results of UCS versus Greedy & A*, in terms of the levels required and the number of nodes expanded. IT HAS TO BE IN PYTHON LANGUAGE