If you mean "Algorithm" an algorithm is simply a set of rules, or steps to complete, which are needed to solve a particular problem. An example would be a recipe in a cookbook. A recipe is an algorithm.
An intractable problem is one for which there is an algorithm that produces a solution - but the algorithm does not produce results in a reasonable amount of time. Intractable problems have a large time complexity. The Travelling Salesman Problem is an example of an intractable problem.
A banana is a non example of rate. They have nothing to do with each other.
Yes. A banana is a non-example of acute. In fact it is also a non-example of an angle!
Yes, you can. Any iterative method/algorithm that is used to solve a continuous mathematics problem can also be called a numerical method/algorithm.
An example of finiteness in algorithm is when a loop within the algorithm has a predetermined number of iterations, meaning it will only run a specific number of times before completing. This ensures that the algorithm will eventually terminate and not run indefinitely.
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A greedy algorithm will return as many results as possible. It depends on the algorithm what that means.An example would be in regular expressions. The regexp "/(a.+b)/" searches for a string that starts with "a" and ends with "b". So in the string "There's a bunny in the basket" a greedy algorithm would find "a bunny in the b", while a non-greedy search would find "a b".
Answer: shortest path routing
Non adaptive algorithm requires any changes to be made manually. Adaptive algorithms are able to make any changes automatically.
If you mean "Algorithm" an algorithm is simply a set of rules, or steps to complete, which are needed to solve a particular problem. An example would be a recipe in a cookbook. A recipe is an algorithm.
4d + 7 = -15
Algorithm is deterministic if for a given input the output generated is same for a function. A mathematical function is deterministic. Hence the state is known at every step of the algorithm.Algorithm is non deterministic if there are more than one path the algorithm can take. Due to this, one cannot determine the next state of the machine running the algorithm. Example would be a random function.FYI,Non deterministic machines that can't solve problems in polynomial time are NP. Hence finding a solution to an NP problem is hard but verifying it can be done in polynomial time. Hope this helps.Pl correct me if I am wrong here.Thank you.Sharada
design an algorithm for finding all the factors of a positive integer
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The formula, as far as I can see, is not appropriate for the algorithm.
i like moldy chess. cheese....shests