Estimating the common agricultural policy milestones and targets by neural networks
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DOI: 10.1016/j.evalprogplan.2023.102296
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References listed on IDEAS
- Sebastian Kujawa & Gniewko Niedbała, 2021. "Artificial Neural Networks in Agriculture," Agriculture, MDPI, vol. 11(6), pages 1-6, May.
- Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.
- Yanyan Fan & Yu Zhang & Baosu Guo & Xiaoyuan Luo & Qingjin Peng & Zhenlin Jin, 2022. "A Hybrid Sparrow Search Algorithm of the Hyperparameter Optimization in Deep Learning," Mathematics, MDPI, vol. 10(16), pages 1-23, August.
- Alwosheel, Ahmad & van Cranenburgh, Sander & Chorus, Caspar G., 2018. "Is your dataset big enough? Sample size requirements when using artificial neural networks for discrete choice analysis," Journal of choice modelling, Elsevier, vol. 28(C), pages 167-182.
- Marko Lovec & Tanja Šumrada & Emil Erjavec, 2020. "New CAP Delivery Model, Old Issues," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 55(2), pages 112-119, March.
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- Dogan, Sedat & Kilicoglu, Cem & Akinci, Halil & Sevik, Hakan & Cetin, Mehmet & Kocan, Nurhan, 2024. "Comprehensive risk assessment for identifying suitable residential zones in Manavgat, Mediterranean Region," Evaluation and Program Planning, Elsevier, vol. 106(C).
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Keywords
2023–2027 Common Agricultural Policy; New Delivery Model; Result indicators; Machine learning; Multilayer feedforward neural networks;All these keywords.
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