Potato Harvesting Prediction Using an Improved ResNet-59 Model

被引:7
作者
Abdelhamid, Abdelaziz A. [1 ]
Alhussan, Amel Ali [2 ]
Qenawy, Al-Seyday T. [3 ,4 ]
Osman, Ahmed M. [5 ]
Elshewey, Ahmed M. [6 ]
Eed, Marwa [7 ,8 ]
机构
[1] Shaqra Univ, Coll Comp & Informat Technol, Dept Comp Sci, Shaqra 11961, Saudi Arabia
[2] Princess Nourah Bint Abdulrahman Univ, Coll Comp & Informat Sci, Dept Comp Sci, POB 84428, Riyadh 11671, Saudi Arabia
[3] Intelligent Syst & Machine Learning Lab, Shenzhen 518000, Peoples R China
[4] Middle East Univ, MEU Res Unit, Amman 11831, Jordan
[5] Suez Univ, Fac Comp & Informat, Dept Informat Syst, POB 43221, Suez, Egypt
[6] Suez Univ, Fac Comp & Informat, Dept Comp Sci, POB 43221, Suez, Egypt
[7] Delta Univ Sci & Technol, Fac Artificial Intelligence, Mansoura 11152, Egypt
[8] Delta Higher Inst Engn & Technol, Mansoura 35111, Egypt
关键词
Artificial intelligence; Deep learning in agriculture; Forecasting; Res-Net59;
D O I
10.1007/s11540-024-09773-6
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
This paper highlights why it is crucial to determine crop production using artificial intelligence for the growth of agriculture. In this paper, an elaborated ResNet-59 model has been developed to estimate potato harvests accurately. The dataset contained a global potato and tomato production data set that began in 1961 and ended in 2021; different deep learning architectures considered were ResNet-59, GoogLeNet, VGG-19, ResNet-50, VGG-16, and MobileNet. Collectively, the outcome of this ResNet-59 model's improvement led to a general superiority with more minor mean squared errors, which were recorded as 0.0083, and a mean absolute error of 0.0762, a median of absolute errors amounted to 0.0750 along with an R2 value equalling 99.05%. According to these results, precision agriculture is another area where ResNet-59 could be effective, thus promoting the rational distribution of resources, minimizing waste and increasing food security. It is epoch-making to deliberate on the capability of artificial intelligence to emancipate sustainable farming and future research.
引用
收藏
页码:1049 / 1068
页数:20
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