Abstract. The algorithm which carries out the multiobjective optimization at realization of the modified clonal selection algorithm based on the use of the notion «Pareto set» when the parental population of antibodies should be created for development of the forecasting models on the base of the strictly binary trees has been offered. Two indicators of quality of the forecasting model -the affinity indicator based on the calculation of the average forecasting error rate, and the tendencies discrepancy indicator -are applied in the role of the objective functions. The results of experimental studies which confirm the efficiency of application of the offered algorithm have been given.
The paper is focused on the forecasting method for time series groups with the use of algorithms for cluster analysis. K-means algorithm is suggested to be a basic one for clustering. The coordinates of the centers of clusters have been put in correspondence with summarizing time series data -the centroids of the clusters. A description of time series, the centroids of the clusters, is implemented with the use of forecasting models. They are based on strict binary trees and a modified clonal selection algorithm. With the help of such forecasting models, the possibility of forming analytic dependences is shown. It is suggested to use a common forecasting model, which is constructed for time series -the centroid of the cluster, in 4814 Nadezhda N. Astakhova et al. forecasting the private (individual) time series in the cluster. The promising application of the suggested method for grouped time series forecasting is demonstrated.
Abstract-The optimization problem dealing with the development of the forecasting models on the base of strictly binary trees has been considered. The aim of paper is the comparative analysis of two optimization variants which are applied for the development of the forecasting models. Herewith the first optimization variant assumes the application of one quality indicator of the forecasting model named as the affinity indicator and the second variant realizes the application of two quality indicators of the forecasting model named as the affinity indicator and the tendencies discrepancy indicator. In both optimization variants the search of the best forecasting models is carried out by means of application of the modified clonal selection algorithm. To obtain the high variety of population of the forecasting models it is offered to consider values of the crowding-distance at the realization of the second optimization variant. The results of experimental studies confirming the use efficiency of the modified clonal selection algorithm on the base of the second optimization variant are given.
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