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What is the difference between greedy algorithm and Divide and Conquer?
greedy method does not give best solution always.but divide and conquer gives the best optimal solution only(for example:quick sort is the best sort).greedy method gives feasible solutions,they need not be optimal at all.divide and conquer and dynamic programming are techniques.
What are the difference between swot analysis and tows matrix?
Tows matrix dynamic and Swot matrix static.
What is the difference between jquery and Ajax?
JQuery is a Javascript code library that helps you do dynamic changes to your website. Ajax has the same idea, but more used to make dynamic changes to your website to and from a database. They really go hand and hand.
Difference between dynamic binding and message passing in tabular form?
| Aspect | Dynamic Binding | Message Passing | |----------------------|------------------------------------------|-------------------------------------------| | Definition | Refers to the runtime decision of which method or function to invoke based on the object's actual type. | Involves sending data or commands between objects or components in a system, typically through a specified protocol. | | Purpose | Enables polymorphism and flexibility in object-oriented programming. | Facilitates communication and interaction between independent entities in a distributed system. | | Mechanism | Achieved through method overriding and virtual function calls. | Implemented using method calls or function invocations that may include parameters or messages. | | Context | Primarily used in object-oriented programming languages. | Commonly used in distributed systems, messaging systems, and network communication. |
What is the difference between dynamic equivalence and formal equivalence?
Dynamic equivalence and formal equivalence are two approaches to translation. Dynamic equivalence focuses on conveying the meaning and intent of the original text in a way that resonates with the target audience, prioritizing comprehension over literal accuracy. In contrast, formal equivalence emphasizes a word-for-word translation, maintaining the original structure and phrasing as closely as possible, even if it makes the text less accessible. Essentially, dynamic equivalence seeks to capture the spirit of the text, while formal equivalence aims for fidelity to the original wording.
What are the difference between greedy algorithm and dynamic programing?
A greedy algorithm is similar to a dynamic programming algorithm, but the difference is that solutions to the subproblems do not have to be known at each stage; instead a "greedy" choice can be made of what looks best for the moment.
Is quick sort is an example of dynamic programming algorithm?
quick sort is a divide and conquer method , it is not dynamic programming
What is the difference between static and dynamic programming?
in static programming properties, methods and object have to be declared first, while in dynamic programming they can be created at runtime. This is usually due to the fact that the dynamic programming language is an interpreted language.
What is the difference between backtracking and dynamic programming?
The only difference between dynamic programming and back tracking is DP allows overlapping of sub problems. (fib(n) = fib(n-1)+ fib (n-2)).
What are the difference between versions and functions?
Version: static reference to a specific entity of a specific instance. Function: dynamic reference to existing algorithm to perform or execute.
What is difference between linear and dynamic programming?
Dynamic programming (DP) has been used to solve a wide range of optimizationproblemsWhen solving a problem using linear programming, specific inequalities involving the inputs are found and then an attempt is made to maximize (or minimize) some linear function of the inputs.
What is difference between dynamic and volumetric compressor?
what is difference between dynamic and volumatic compressor
How can envelope condition be effectively utilized in dynamic programming?
In dynamic programming, envelope condition can be effectively utilized by ensuring that the optimal solution to a subproblem is contained within the optimal solutions of larger subproblems. This helps in reducing the number of redundant calculations and improving the efficiency of the algorithm.
What is the difference between greedy algorithm and Divide and Conquer?
greedy method does not give best solution always.but divide and conquer gives the best optimal solution only(for example:quick sort is the best sort).greedy method gives feasible solutions,they need not be optimal at all.divide and conquer and dynamic programming are techniques.
What is the minimum coin change problem and how is it typically approached in the field of computer science?
The minimum coin change problem is a mathematical problem where the goal is to find the fewest number of coins needed to make a certain amount of change. In computer science, this problem is typically approached using dynamic programming algorithms, such as the greedy algorithm or the dynamic programming algorithm, to efficiently find the optimal solution.
What is the most efficient dynamic programming solution for breaking a string into smaller substrings?
The most efficient dynamic programming solution for breaking a string into smaller substrings is the "memoization" technique. This involves storing the results of subproblems in a table to avoid redundant calculations, which can significantly improve the efficiency of the algorithm.
Who one of the following algorithm is used in finding shortest distance in a graphs -a) dynamic programming b)greedy method c)backtracking d)divide and conquer?
One of the algorithms used for finding the shortest distance in graphs is the greedy method, specifically Dijkstra's algorithm. This algorithm works by selecting the vertex with the smallest known distance, updating the distances to its neighboring vertices, and repeating the process until all vertices are processed. While dynamic programming can also be utilized in certain shortest path algorithms like the Floyd-Warshall algorithm, the greedy approach is more commonly associated with this specific problem.
