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基于水波优化的模糊估计作物种植规划

Crop cultivation planning with fuzzy estimation using water wave optimization.

作者信息

Liu Li-Chang, Lv Kang-Cong, Zheng Yu-Jun

机构信息

School of Information Science and Technology, Hangzhou Normal University, Hangzhou, Zhejiang, China.

出版信息

Front Plant Sci. 2023 Mar 6;14:1139094. doi: 10.3389/fpls.2023.1139094. eCollection 2023.

Abstract

In a complex agricultural region, determine the appropriate crop for each plot of land to maximize the expected total profit is the key problem in cultivation management. However, many factors such as cost, yield, and selling price are typically uncertain, which causes an exact programming method impractical. In this paper, we present a problem of crop cultivation planning, where the uncertain factors are estimated as fuzzy parameters. We adapt an efficient evolutionary algorithm, water wave optimization (WWO), to solve this problem, where each solution is evaluated based on three metrics including the expected, optimistic and pessimistic values, the combination of which enables the algorithm to search credible solutions under uncertain conditions. Test results on a set of agricultural regions in East China showed that the solutions of our fuzzy optimization approach obtained significantly higher profits than those of non-fuzzy optimization methods based on only the expected values.

摘要

在一个复杂的农业区域,确定每块土地适合种植的作物以实现预期总利润最大化是种植管理中的关键问题。然而,成本、产量和售价等诸多因素通常具有不确定性,这使得精确的规划方法不切实际。在本文中,我们提出了一个作物种植规划问题,其中将不确定因素估计为模糊参数。我们采用一种高效的进化算法——水波优化算法(WWO)来解决这个问题,每个解基于包括期望值、乐观值和悲观值在内的三个指标进行评估,这三个指标的组合使该算法能够在不确定条件下搜索可靠的解。对华东地区一组农业区域的测试结果表明,我们的模糊优化方法得到的解所获得的利润显著高于仅基于期望值的非模糊优化方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ce8/10027006/ee98b4e1067b/fpls-14-1139094-g001.jpg

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