SPORTS ECOTOURISM DEMAND PREDICTION USING IMPROVED FRUIT FLY OPTIMIZATION ALGORITHM
DOI:
https://doi.org/10.23055/ijietap.2023.30.6.8841Keywords:
sports, eco-tourism, improved FOA algorithmAbstract
With improvements in the national consumption level, the tourism industry is playing an increasingly important role in the national economy, and the proportion of tourism revenue in GDP is constantly increasing. In this paper, we first improve the standard Drosophila algorithm by adaptively adjusting the fly population number and search step size while optimizing the initial iteration position and improving the local search ability and search efficiency. Then, the improved algorithm (FOA) is combined with the echo state network to establish a two-stage combined prediction model called the Adaptive Fruit Fly Optimization Algorithm-Echo State Network (AFOA-ESN). The experimental results show that the AFOA-ESN model has higher prediction accuracy compared to other prediction models, and the convergence rate and prediction accuracy of the AFOA-ESN are better than the standard ESN and FOA-ESN, proving the effectiveness of model improvement.
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