A systematic literature review on machine learning applications for sustainable agriculture supply chain performance
From MaRDI portal
Publication:2177820
DOI10.1016/j.cor.2020.104926zbMath1458.90139OpenAlexW3007397514MaRDI QIDQ2177820
Vikas Kumar, Rohit Sharma, Anil Kumar, Sachin S. Kamble, Angappa Gunasekaran
Publication date: 6 May 2020
Published in: Computers \& Operations Research (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10545/624595
Learning and adaptive systems in artificial intelligence (68T05) Transportation, logistics and supply chain management (90B06)
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Cites Work
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- A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs
- A dynamic stochastic programming model of crop rotation choice to test the adoption of long rotation under price and production risks
- A multi-period ordering and clearance pricing model considering the competition between new and out-of-season products
- A decision support system for vine growers based on a Bayesian network
- A survey of data mining techniques applied to agriculture
- A bi-objective aggregate production planning problem with learning effect and machine deterioration: modeling and solution
- Integrated production and distribution scheduling with a perishable product
- Neural network imputation: an experience with the national resources inventory survey
- Application of planning models in the agri-food supply chain: A review
- Artificial neural networks and multicriterion analysis for sustainable irrigation planning
- Machine learning: Trends, perspectives, and prospects
- Introduction to Semi-Supervised Learning
- Dynamic allocation of uncertain supply for the perishable commodity supply chain
- Analysing organic food buyers' perceptions with Bayesian networks: a case study in Turkey
- Food shelf life: estimation and optimal design
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