Demand Prediction with Multi-Stage Neural Processing
نویسندگان
چکیده
In many technical issues, the processes of interest could be precisely modelled if only all the relevant information were available. On the other hand, detailed modelling is frequently not feasible due to the cost of acquiring appropriate data. The paper discusses the way self-organising maps and multilayer perceptrons can be used to develop two-stage algorithm for autonomous construction of prediction models. The problem used as a case study is the problem of heat demand prediction in a district heating company. Additionally, because of non-standard evaluation of prediction models, evolutionary construction of multilayer perceptrons has been applied.
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