@article{article_1757092, title={Hybrid Deep Learning Model for Predicting the Contribution of SMEs to the Economy: A Case Study for Turkey}, journal={Journal of Soft Computing and Artificial Intelligence}, volume={6}, pages={1–19}, DOI={10.55195/jscai.1757092}, author={Utku, Anıl and Sevinç, Ali and Akcayol, M. Ali}, keywords={SME, Economy, Deep learning, Machine learning}, abstract={In this study, a combination of deep learning models was developed to calculate the economic contribution of SMEs. The hybrid model’s advantage lies in its ability to leverage the strengths of CNN to identify spatial relationships and draw patterns, as well as LSTM to capture sequential temporal dependencies. The goal of this hybrid model was to provide an accurate estimate of the economic contribution of SMEs. To compare the effectiveness of the hybrid model, extensive comparative experiments were conducted using a dataset of economic indicators of SMEs in Tadrakea. The experiments demonstrated that CNN-LSTM outperforms other commonly used machine learning and deep learning networks. A hybrid model, combining CNN and LSTM, can be used to capture complex data, thereby improving prediction accuracy.}, number={2}, publisher={Mahmud ASİLSOY}