That depends how the data is stored. If you use predesigend classes to store information about nodes and edges, check the documentation of the specific class or classes. Or ask a question here, specifiying the class you are using.
# Initialise the graph to start node # Traverse the graph following the current path accumulating nodes that have not yet been expanded or solved # Pick any of these nodes and expand it and if it has no successors call this value FUTILITY otherwise calculate only f' for each of the successors. # If f' is 0 then mark the node as SOLVED # Change the value of f' for the newly created node to reflect its successors by back propagation. # Wherever possible use the most promising routes and if a node is marked as SOLVED then mark the parent node as SOLVED. # If starting node is SOLVED or value greater than FUTILITY, stop, else repeat from 2.
Primarily it allows implementation to be shifted from the list to the nodes themselves. Generally this is more efficient because the list's sole responsibility is the sentinel (which is guaranteed to exist so long as the list is in scope) to which it delegates all responsibility with regards the actual nodes. A tail sentinel improves efficiency further by ensuring the head sentinel node never points to NULL. Head and tail sentinels are most useful in sorted lists. When data is added to the list, the list immediately passes the data to the head node. When the head node receives data it immediately passes it to the next node, and sets its next node to the return value. The data passes from one node to the next until it reaches a node that contains larger data, or it reaches the tail sentinel. Either way, a new node is created such that it points to the current node, and returns the new node to the calling node which updates its next node to point to the new node. All previous nodes remain unchanged by returning themselves to the calling nodes, all the way back to the head. This is more efficient than using a non-sentinel list. With this implementation, the list itself must traverse the nodes (if any) to locate the insertion point and then update the links between the nodes. This is because if there are no nodes, the list must handle the insertion itself. Therefore it must handle all insertions, nodes or not. in other words, sentinel nodes shift the responsibility for insertion to the nodes themselves. Since traversal is required anyway, it makes sense to reduce the level of indirection and let the nodes sort themselves out, rather than forcing them into order by a class that has no inherent knowledge of the data it is trying to insert. Data sorting is the responsibility of the nodes that contain it, not the list itself.
No. A leaf node is a node that has no child nodes. A null node is a node pointer that points to the null address (address zero). Since a leaf node has no children, its child nodes are null nodes.
A binary search tree uses the definition: that for every node,the node to the left of it has a less value(key) and the node to the right of it has a greater value(key).Where as the heap,being an implementation of a binary tree uses the following definition:If A and B are nodes, where B is the child node of A,then the value(key) of A must be larger than or equal to the value(key) of B.That is,key(A) ≥ key(B).
Assuming that the voltage between two nodes are the same, current changes with branches. If you add branches, this means the current will be divided, depending on the resistance strength. Greater the resistance, the lower the current. If there is no resistance, it will end up in a short circuit, getting all the current. If there is great resistance, there will be very little current passing. Mathematically, V=I*R is the formula. If you know the voltage between two nodes, you can calculate the currency (I) in each branch and for the whole nodes by putting in the particular resistance value for the branch or the whole nodes.
Line graph- two axis, plot the graph with each points (e.g 2,4) and join them up with a straight or curve line Bar graph- Drawn using bars Pie graph- circle of 360 degrees and divide each section measured according to the given value
The absolute value of the difference.
rise
It tells you the relationship between the X value and the Y value is constant.
An ordered value bar graph is a value bar graph in which data values are arranged in increasing (or decreasing) order of length.
Take the largest value in the graph and subtract the smallest value from it.
a graph that shows the data.
Graph (data structure) A labeled graph of 6 vertices and 7 edges.In computer science, a graph is an abstract data structure that is meant to implement the graph concept from mathematics.A graph data structure consists mainly of a finite (and possibly mutable) set of ordered pairs, called edges or arcs, of certain entities called nodes or vertices. As in mathematics, an edge (x,y) is said to point or go from x to y. The nodes may be part of the graph structure, or may be external entities represented by integer indices or references.A graph data structure may also associate to each edge some edge value, such as a symbolic label or a numeric attribute (cost, capacity, length, etc.).
The x value and the y value are directly and invertly related on a graph. This only occurs in a specific type of graph called a proportional graph.
That is a result of an absolute value equation. So an Absolute Value Graph
Because of the word "cumulative". What that means is that the height of the graph for any value (X=x) is the number (or proportion) of observations that were less than or equal to the value x. Now consider the cumulative value of the graph for a value of X which is bigger than x. All the previous observations were ≤ x and so they will be ≤ the newer, larger value. So the height of the cumulative graph cannot decrease. It may increase if there are any observations whose value was between x and the new value.
The slope of a graph provides general information about a graph. It tells you how much the y value of the graph increases (or decreases, if the slope is negative) for a given increase in x value. if you look at the general equation of a graph y = a x + b the value "a" represents the slope and the "b" value represents the value of y when x = 0. When the graph is not a straight line, the discussion gets more complicated, however the slope still describes changes in the value of the graph (you have to use calculus for this situation.)