Abstract
This paper introduced detailed the design of intelligent system for decision-making. Firstly, the overall design of grassland degradation decision-making system of Sanjiangyuan based on neural network is carried out, including man–machine interface module, knowledge base module, neural network module and inference engine module. Secondly, the specific functions of each module are introduced. Finally, the design of neural network was introduced detailed, the entire BP neural network consists of three layers of structure. There are five nodes in the input layer, five nodes in the output layer, and six nodes in the hidden layer.
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Li, X-l, Perry, L.W.G., Brierley, G., et al.: Restoration prospects for Heitutan degraded grassland in the Sanjiangyuan. J. Mt. Sci. 10(4), 687–698 (2013)
Wu, L., Wang, H.: Poisoning the pika: must protection of grasslands be at the expense of biodiversity? Sci. China Life Sci. 60(5), 545–547 (2017)
Liu, S., Tang, Y., Zhang, F., et al.: Global estimates of the impacts of grassland degradation on livestock productivity from 2001 to 2011. In: Economics of Land Degradation and Improvement, pp. 197–214. Springer, Cham (2016)
Su, X-k, Wu, Y., Dong, S-k, et al.: Effects of grassland degradation and re-vegetation on carbon and nitrogen storage in the soils of the Headwater Area Nature Reserve on the Qinghai–Tibetan Plateau. J. Mt. Sci. 22(3), 582–591 (2015)
Cheng, Y., Wu, R.: The research of aviation dangerous weather forecast for fog and haze based on BP neural network. In: Proceedings of the 5th International Conference on Electrical Engineering and Automatic Control, pp. 877–883 (2016)
Huang, C., Li, L., Ren, S., et al.: Research of soil moisture content forecast model based on genetic algorithm BP neural network. In: International Conference on Computer and Computing Technologies in Agriculture, Computer and Computing Technologies in Agriculture II, vol. 2, pp. 1209–1216 (2011)
Song, D., Han, B.: Avionic fault diagnosis expert system based on flight data and BIT information. In: Proceedings of the First Symposium on Aviation Maintenance and Management, pp. 303–311 (2014)
Blahuta, J., Soukup, T., Martinu, J.: An expert system based on using artificial neural network and region-based image processing to recognition substantia nigra and atherosclerotic plaques in B-images: a prospective study. In: International Work-Conference on Artificial Neural Networks, Advances in Computational Intelligence, pp. 236–245 (2017)
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The authors acknowledge the Science and Technology Department of Qinghai Province China (Grant 2016-ZJ-774).
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Li, C., Wang, Y., Fang, T. et al. A neural network decision expert system for alpine meadow degradation in the Sanjiangyuan region. Cluster Comput 22 (Suppl 4), 8193–8198 (2019). https://doi.org/10.1007/s10586-018-1698-x
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DOI: https://doi.org/10.1007/s10586-018-1698-x