Hello, Gattaka, you wrote: G> Colleagues, G> It is necessary to predict sequence of events in time. We assume to eat events ' A ', ' B ', ' a C ' etc. the Latin alphabet. G> these events happen in time so that chain G> G> ABCDABDSSABCSSABCSS G> To me this chain is formed it is necessary to continue. As you can see in an example of all some events A, B, a C, D, SS. And it is easy to note that ABC, AB - follow one after another. I.e. if event A it is possible to state with high probability approach BC and so on. Events Z, F, K - do not meet at all. G> for each event there is an approach date. How such tasks dare? Circuits ? neural networks? G> to Vprintsipe on answers for the task above - I will be already grateful. But actually the task is more difficult. To each event at its approach the number from 1 to 0 - fractional is compared. And I need to predict this number. Normally tasks such do not dare. Because it is a lot of unknown persons. Normally to be under construction model which gives adequate accuracy of a prediction. For model creation it is necessary to understand: 1) whether only events Depend on the previous events or not? If yes, whether that are identical weight? 2) whether probabilities in time Change or not? 3) whether there is inside latent process having more of states, than observable events? If probabilities in time do not change, and following event depends only from previous, model - a circuit . The matrix of approach of events is stood, in any point it is possible to predict following events and probability of a chain. If depends on several previous - that in lines of a matrix will be not one previous event, and sequence. If not equiprobablly depends from previous it is necessary to select weight. If inside more difficult mechanism already it is necessary to use the Latent Markov Model. If events concern the order it is possible to use methods of the technical analysis from trading.