Search results
Results from the WOW.Com Content Network
It iteratively does hill-climbing, each time with a random initial condition . The best is kept: if a new run of hill climbing produces a better than the stored state, it replaces the stored state. Random-restart hill climbing is a surprisingly effective algorithm in many cases.
Mean-shift is a hill climbing algorithm which involves shifting this kernel iteratively to a higher density region until convergence. Every shift is defined by a mean shift vector. The mean shift vector always points toward the direction of the maximum increase in the density.
The change in altitude over the climb (measured in metres or feet). length_m length_ft length_km length_mi: The length of the climb (measured in metres, feet, kilometres or miles). max_elevation_m max_elevation_ft: Maximum height above mean sea level (measured in metres or feet) gradient: Average gradient along the climb given as a percentage.
Iterated Local Search [1] [2] (ILS) is a term in applied mathematics and computer science defining a modification of local search or hill climbing methods for solving discrete optimization problems. Local search methods can get stuck in a local minimum, where no improving neighbors are available.
Main page; Contents; Current events; Random article; About Wikipedia; Contact us
Local search is an anytime algorithm; it can return a valid solution even if it's interrupted at any time after finding the first valid solution. Local search is typically an approximation or incomplete algorithm because the search may stop even if the current best solution found is not optimal. This can happen even if termination happens ...
What links here; Related changes; Upload file; Special pages; Permanent link; Page information; Cite this page; Get shortened URL; Download QR code
Stochastic hill climbing is a variant of the basic hill climbing method. While basic hill climbing always chooses the steepest uphill move, "stochastic hill climbing chooses at random from among the uphill moves; the probability of selection can vary with the steepness of the uphill move."