E-agricultural system based intelligent predictive analysis and smart farming with digitalized demand and supply utilization to maximize the yield rate of crops using machine learning algorithm
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Abstract
Agriculture is one of the essential supplements of our society. Soil is essential to related agriculture. The composition of soil differs from soil to soil. The Growth of Crops is laid low with those chemical capabilities of soil. Choosing the proper sort of vegetation for that specific sort of soil is likewise essential. Machine Learning strategies may be used to categorise the soil collection statistics this undertaking provides a soil retrieval device which takes enter photograph as a Soil pictures taken from vicinity Using Deep gaining knowledge of set of rules to categorise soil and additionally advise the crop info and offer the weather condition. Many farmers lack cash and want to get rid of their products as soon as possible. This means that even if the harvest is good, farmers may run into trouble if the harvest cannot be delivered outside the town. Your product must also be delivered to consumers within a reasonable time frame at a reasonable cost.
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How to Cite
et. al., D. A. S. M. . (2021). E-agricultural system based intelligent predictive analysis and smart farming with digitalized demand and supply utilization to maximize the yield rate of crops using machine learning algorithm. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 2036–2041. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/4712
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Research Articles
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