Selected article for: "positive value and zero value"

Author: Livio Fenga; Carlo Del Castello
Title: CoViD19 Meta heuristic optimization based forecast method on time dependent bootstrapped data
  • Document date: 2020_4_7
  • ID: j1p4nmsa_32
    Snippet: In general, simulated annealing algorithms work as below explained. The temperature progressively decreases from an initial positive value to zero. At each time step, the algorithm randomly selects some neighbor state s * of the current state s, measures its energy (in this case the M SE i (x * t,i ) on the bootstrap distribution) and decides between moving the system to the state s * or staying in state s according to the temperature-dependent p.....
    Document: In general, simulated annealing algorithms work as below explained. The temperature progressively decreases from an initial positive value to zero. At each time step, the algorithm randomly selects some neighbor state s * of the current state s, measures its energy (in this case the M SE i (x * t,i ) on the bootstrap distribution) and decides between moving the system to the state s * or staying in state s according to the temperature-dependent probabilities of selecting better or worse solutions, which during the search respectively remain at 1 (or positive) and decrease towards zero.

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