Citation

Jayaram, Jayapradha and Haw, Su Cheng and Hemanth, Ganga and Dave, Tejal and Kumar, T. Senthil (2025) Development of AI-ML based models for predicting prices of agri-horticulture commodities such as pulses and vegetable. In: 9th International Conference on Smart Internet of Things, SmartIoT 2025, 17 November 2025 - 20 November 2025, Sydney.

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Abstract

Agriculture is a critical sector in world economies, especially in developing countries, where price volatility of agrihorticultural crops such as pulses and vegetables is a major challenge for farmers, traders, and policymakers. The objective of this work is to create AI-ML-based forecasting models to predict commodity prices with high accuracy using historical price data, market trends, and external factors like weather conditions, demand-supply balance, and policy interventions. The incorporation of sophisticated machine learning algorithms, including the Elastic Net model, maximizes prediction accuracy, allowing decision-makers to make sound decisions on production and marketing strategies. The improvement in market transparency and economic risk reduction enables farmers to optimize resource reallocation, avoid wastage, and promote a more stable and sustainable agriculture value chain.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Price prediction, machine learning,
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	18 Mar 2026 05:11
Last Modified:	18 Mar 2026 06:38
URII:	http://shdl.mmu.edu.my/id/eprint/15550

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