local optimum वाक्य
उदाहरण वाक्य
मोबाइल
- This is why the best solution found by such algorithms is called a local optimum in contrast with the actual best solution which is called a global optimum.
- A good training set should be representative of the problem at hand and also well-balanced, otherwise the algorithm might get stuck at some local optimum.
- Unfortunately, it generally takes an exponential number of improvement steps to find a local optimum even if the problem L can be solved exactly in polynomial time.
- :The original question was sensible, except that it should have used a term such as " local optimum " instead of " apex of evolution ".
- The problem is computationally difficult ( NP-hard ); however, there are efficient heuristic algorithms that are commonly employed and converge quickly to a local optimum.
- For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to alternatives such as gradient descent.
- A convex objective function that is to be maximized, it will generally be easier to solve in the presence of a convex feasible set and any local optimum will also be a global optimum.
- For problems where finding the precise global optimum is less important than finding an acceptable local optimum in a fixed amount of time, simulated annealing may be preferable to alternatives such as gradient descent.
- Like many inference problems, the solutions to inferring the two variables together can be found, to a local optimum solution, by alternating updates of the two beliefs in a form of EM algorithm.
- Hill climbing by itself isn't guaranteed to find the optimum solution, just a " local optimum " ( the top of your hill may not be the highest point in the world ).
- For a given constraint there may also exist several minimal surfaces with different areas ( for example, see minimal surface of revolution ) : the standard definitions only relate to a local optimum, not a global optimum.
- In applied mathematics and computer science, a "'local optimum "'of an optimization problem is a solution that is optimal ( either all possible solutions, not just those in a particular neighborhood of values.
- Slightly more complex algorithms rely on local optimization to reach a local optimum of a placement evaluation function in each iteration placement of a single label is moved to another position, and if it improves the result, the move is preserved.
- It's only guaranteed to find the global optimum solution if it's also the only local optimum, which it tends not to be in interesting problems .-- talk ) 20 : 49, 29 October 2012 ( UTC)
- Locust swarms are based on a " devour and move on " strategy after a sub-swarm " devours " a relatively small region of the search space ( to find a local optimum ) scouts are deployed to look for new promising regions to " move on ".
- This school of thought has been prevalent since the inception of PSO . This school of thought contends that the PSO algorithm and its parameters must be chosen so as to properly balance between exploration and exploitation to avoid premature convergence to a local optimum yet still ensure a good rate of below.
- Note that'iterative repair', unlike the'backtracking'search outlined above, does not guarantee a solution : like all hillclimbing ( i . e ., greedy ) procedures, it may get stuck on a local optimum ( in which case the algorithm may be restarted with a different initial configuration ).
- Hill climbing is good for finding a local optimum ( a solution that cannot be improved by considering a neighbouring configuration ) but it is not necessarily guaranteed to find the best possible solution ( the global optimum ) out of all possible solutions ( the convex problems, hill-climbing " is " optimal.
- One of the significant ways in which evolution is " not " intelligent is that while it's very good at blindly finding its way to a local optimum or maximum, it's very bad at stepping back, getting the " big picture ", and trying a completely different approach that would let it reach some other, and much higher, optimum or maximum . ( Although on the other hand, us supposedly intelligent humans aren't always so hot at doing this, either . ) talk ) 05 : 51, 8 March 2006 ( UTC)
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