Sustain our Variable Population Through Differential Evolution Algorithm and Agriculture Innovation
A. Ranjeeth1, M. Sujitha2

1A. Ranjeeth, Assistant Professor, Department of Computer Science and Engineering, IFET College of Engineering Villupuram (Tamil Nadu), India.
2M. Sujitha, UG Scholar, Department of Computer Science and Engineering, IFET College of Engineering Villupuram (Tamil Nadu), India.  
Manuscript received on 15 July 2022 | Revised Manuscript received on 21 July 2022 | Manuscript Accepted on 15 August 2022 | Manuscript published on 30 August 2022 | PP: 36-39 | Volume-11 Issue-9, August 2022 | Retrieval Number: 100.1/ijitee.G92130811922 | DOI: 10.35940/ijitee.G9213.0811922
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Abstract: Agriculture is a subdivision that provides considerably to the business-related incident of our country. As the world’s population grows, Agricultural production has overtaken all other industries as its most significant source of growth. Because the need for food was lower in the 1970’s due to a smaller population compared to today’s population statistics, that think that the world’s public will extend to 9.9 billion by 2050, humanity must plan for agricultural production to feed these exponentially growing numbers. Therefore, we need huge agricultural lands to produce the grains and crops necessary for the current population. But much of the formerly arable land has been abandoned during periods of drought, and due to poor planning and poor water management during the dry season, saving arable land from drought is inevitable. Making a structured plan for water management can be one solution to mitigating large amounts of farmland disappearing. Only 12% of the land can be used for agriculture, but we need to feed 9.9 billion people 70% more food by 2050. That’s enough to feed 10 billion people (we’re at 7.6 billion right now). Despite this excess, hunger persisted. So we have come up with the Differential Evolution Algorithm, which predicts the future population’s food needs based on past and present agricultural data. This helps to solve hunger in the near future and also helps limit drought on land. This study aims to highlight the importance of agricultural information systems for agricultural development, identify the strengths and weaknesses of current systems, and provide recommendations for improving their performance. We will return to the results of previous studies on this issue. Finally, general conclusions about farm information systems are highlighted, suggesting implications for better farm information systems.
Keywords: Agriculture, Differential Evolution Algorithm, population, predict
Scope of the Article: Sustainable Structures