Μετάφραση και ανάλυση λέξεων από τεχνητή νοημοσύνη
Σε αυτήν τη σελίδα μπορείτε να λάβετε μια λεπτομερή ανάλυση μιας λέξης ή μιας φράσης, η οποία δημιουργήθηκε χρησιμοποιώντας το ChatGPT, την καλύτερη τεχνολογία τεχνητής νοημοσύνης μέχρι σήμερα:
- πώς χρησιμοποιείται η λέξη
- συχνότητα χρήσης
- χρησιμοποιείται πιο συχνά στον προφορικό ή γραπτό λόγο
- επιλογές μετάφρασης λέξεων
- παραδείγματα χρήσης (πολλές φράσεις με μετάφραση)
- ετυμολογία
Τι (ποιος) είναι overlapping period - ορισμός
![latent period]], the infectious period (the period of communicability) and the [[incubation period]]. In some diseases, as depicted in this diagram, the latent period is shorter than the incubation period. A person can transmit an infection without showing any signs of the disease. Such an infection is called a [[subclinical infection]].](https://commons.wikimedia.org/wiki/Special:FilePath/Concept of incubation period.svg?width=200 "latent period]], the infectious period (the period of communicability) and the [[incubation period]]. In some diseases, as depicted in this diagram, the latent period is shorter than the incubation period. A person can transmit an infection without showing any signs of the disease. Such an infection is called a [[subclinical infection]].")
Βικιπαίδεια
In computer science, a problem is said to have overlapping subproblems if the problem can be broken down into subproblems which are reused several times or a recursive algorithm for the problem solves the same subproblem over and over rather than always generating new subproblems.
For example, the problem of computing the Fibonacci sequence exhibits overlapping subproblems. The problem of computing the nth Fibonacci number F(n), can be broken down into the subproblems of computing F(n − 1) and F(n − 2), and then adding the two. The subproblem of computing F(n − 1) can itself be broken down into a subproblem that involves computing F(n − 2). Therefore, the computation of F(n − 2) is reused, and the Fibonacci sequence thus exhibits overlapping subproblems.
A naive recursive approach to such a problem generally fails due to an exponential complexity. If the problem also shares an optimal substructure property, dynamic programming is a good way to work it out.
