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Q: Is linear data structure is better than non linear data structure?

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A linear data structure has a single path from the first element to the last. Thus arrays and lists are linear structures. A non-linear data structure has one or more "branches"; forks in the road. This means there is more than one route through the structure and there may be more than one endpoint. A binary tree is an example of a non-linear data structure.

Linear Data Structure:-A data structure in which every element has got exactly two neighbors or two adjacent elements except two elements having exactly one data element.Non-Linear Data Structure:- In non linear data elements are allowed to have more than two adjacent elements.

Data Structure - Arrangement of data in computer memory. One of several ways of categorizing data structures is to distinguish between linear and non-linear data structure. A linear data structure is one where there is one unambiguous way to progress from one element N to its successor or predecessor element. Single-dimensional arrays, simple lists or rings, stacks and queues are all examples for linear data structures. A nonlinear is one where one element can be connected to more than one element for each direction of operation (no more than two neighbors, one successor and one predecessor). Multi-dimensional arrays, trees and graphs are examples for non-linear data structures.

If the data is unsorted, or the records' size are variable, or only sequential access is possible, then linear search is much better than binary search. (Because the latter is unusable.)

When binary search is not possible. For example: unsorted data, data with variable length, only sequentially accessible data (tape).

When we speak of linear and no-linear data structures, we are referring to the links between one element and the next. These links determine how we traverse the structure such that we "visit" every element in the structure. When every element has only one possible link to the next in sequence, then the structure is said to be linear. If any element has two or more possible links, it is said to be non-linear. Arrays, lists, stack and queues are examples of linear structures. Trees, networks and graphs are examples of non-linear structures. A binary tree is the simplest example of a non-linear structure because every element has, at most, two possible links, a left link and a right link. If we follow the left link, then at some point we must return to that same element in order to follow its right link. This means we must backtrack. Any structure that requires us to backtrack during a traversal is therefore non-linear. Linear traversal is more efficient than non-linear traversal because there is no need to backtrack to traverse a linear data structure.

With linear data structures, you traverse from one end of the structure to the other, visiting every element in the structure no more than once. Linear structures may be bi-directional, thus you may start from either end, but regardless of the direction of traversal there is only one possible route to reach the other end. With non-linear data structures there may be any number of routes through the structure. That is, at any element you might have a choice of one or more possible routes. If there is more than one, then at some point you will have to backtrack to that element in order to traverse those other routes, unless a route just happens to link back to that element. However, non-linear structures may also have a choice of start and end points. That is, you may choose to start from any element but your route through the elements will ultimately determine where you end. Linear and non-linear structures are typified by "travelling salesman" problems, where a salesman must visit a number of locations throughout a town using the shortest possible route. If he can achieve that without any backtracking then the route is linear and can therefore be modelled using a linear structure. Otherwise it is non-linear and must be modelled using a non-linear structure. Analysis of that structure will then determine the optimum routes. Linear structures are typically modelled using arrays and lists. Non-linear structures are typically modelled using trees and graphs.

Protein tertiary structure is 3-D. Secondary structure is 2-D or linear. I. e. the linear a-a sequence is the secondary structure. Amino-acid monomers comprise the primary structure.

The cystalline branched polyethylene has got a complex structure than a linear polyethylene.

Yes, specific data is better than general data if it is accurate. General data can be inferred from specific data.

Are computers better data processors than humans

A non-linear data structure is any structure where traversal through a network of nodes may have more than one route. If we think of a linear data structure as being a row of houses along a road, we simply traverse the road to visit each house in turn. With a non-linear structure, the road will periodically fork or branch, offering multiple routes. Whenever we traverse down one of those routes, there's always the possibility we must backtrack to that point in order to traverse the alternative routes. This means we may visit some houses more than once. However, when we're backtracking, we don't actually have to visit houses we've already visited, we simply walk past them until we reach a point where there is an alternative route that has yet to be traversed. In order to keep track of our route through a non-linear structure, we must lay down a trail of breadcrumbs. Whenever we backtrack to a point where there are one or more routes without breadcrumbs, we traverse down one of those routes.

It is better than keeping unreliable data!

no it is not

Dvd is better than CD because the dvd can store more data than the CD

harder to implement than linear queue,but once you understand the concept it utilizes memory in a very much better way than linear queue.

Specific data gives you more information and is more reliable.

Linear search is the only way to search an unsorted data sequence. However, the data sequence can be broken up into equal parts that can be searched independently using multiple threads. Thus a processor with 4 cores can potentially execute a linear search 4 times quicker than a single thread could.

Data structure is nothing but a way to organize and manipulate any given set of data in a specific and reusable format/structure hence simplifying the manipulation of data. Some of the commonly and frequently used data structures are Stack, Queue, List, Set, e.t.c. But this list is not limited to what we see here, rather we can invent our own as long as there is a definite structure and better efficiency by using it than work with raw data.

To copy a structure you simply allocate the amount of memory required to store the structure. For simple data structures like arrays that's all you need to do (leaving the memory uninitialised or set to some default value such as zero). But for complex structures like lists, trees and graphs, you need to recreate the links between the nodes within the allocated memory. If the original structure is not allocated in contiguous memory, this can be more trouble than it is actually worth. A simpler approach would be to rebuild the structure one node at a time, using the node's default value for the data. This can be simplified further by separating the data from the structure, so that the structure simply refers to the data rather than stores the data.

yes, but it requires that the data be entered originally in a searchable tree format.

to analysis the theory perfectly and give concerned answers

A linear data structure is any data structure where the data elements can be easily traversed from one end to the other in a single pass, visiting each element exactly once. An array is the simplest linear data structure because the memory layout determines the sequence and we can traverse the sequence in either direction very efficiently. Lists are more complex in that every element must maintain a link to the next element in the sequence. To traverse in both directions, two links per element are required, one to the next element and one to the previous element. While we typically don't want to allow linear traversal of a stack or queue, they are still linear structures because elements are pushed onto a queue from the back and popped off from the front while stacks push and pop from the same end. Either way, the order of the elements from one to the next is linear. Non-linear data structures are more complex than linear structures because one element may link to two or more elements. A tree is a typical example because while an element can have only one parent element (the previous element), it can have any number of child elements, any one of which can be regarded as being the "next" element in the sequence. Moreover, while a linear sequence has only one end point, a tree may have many end points, known as leafs (elements with no children), and each must be fully explored to ensure we visit every element at least once. Graphs are even more complex because there is no parent-child relationship between links, never mind a next-previous relationship. Graph links can even loop back to previously visited elements.

you can visualize the graph better than the table. ---------------------------------------------------- A data can make A PATTERN much easier to recognize and understand.

A non-linear graph. It could be a polynomial (of a degree greater than 1), a power function, a logarithmic or trigonometric graph. In fact any mathematical function other than a linear equation.