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相关概念视频

Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

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Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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相关实验视频

Updated: Jun 13, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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用生物灵感算法对作物土地分配问题进行中性学目标编程技术.

S Angammal1, G Hannah Grace2

  • 1School of Advanced Sciences, Department of Mathematics, Vellore Institute of Technology Chennai, Chennai, 6000127, India.

Scientific reports
|September 16, 2024
PubMed
概括

这项研究介绍了中性学目标编程 (NGP) 与生物启发的算法,以优化农业用地分配,最大限度地提高利和产出在不确定性. 这种新方法的性能优于现有的技术,可以改善农场管理.

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科学领域:

  • 农业经济学 农业经济学
  • 运营研究 运营研究
  • 计算智能是一种计算智能.

背景情况:

  • 土地分配和作物规划在农业中至关重要,面对产量,价格和不确定的因素的不确定性.
  • 现有的模糊和直观的模糊优化方法缺乏不确定性会员功能.
  • 中性学优化独特地结合了真理,虚假和不确定性成员功能,以改善决策.

研究的目的:

  • 通过中性学目标编程 (NGP) 加强农业用地分配和作物规划.
  • 将六角直觉参数和高级会员函数 (超标,指数,线性) 纳入NGP.
  • 通过尽量减少真理,不确定性和虚假的偏差来优化支出,生产和利.

主要方法:

  • 开发了一个NGP模型,具有六角直觉参数和新的会员功能.
  • 集成的生物灵感算法灰狼优化 (GWO),社会群体优化 (SGO) 和粒子群体优化 (PSO) 解决NGP成就函数.
  • 收集印度泰米尔纳德州阿里亚卢尔区中型农民的数据.

主要成果:

  • 与Zimmermann,Angelov和Torabi技术相比,采用生物灵感算法提出的NGP方法实现了优越的最佳解决方案.
  • 证明了将真实,不确定性和虚假的成员函数用于农业优化的有效性.
  • 生物灵感算法成功导航复杂的解决方案空间,以找到NGP实现函数的全球最佳.

结论:

  • 与生物灵感算法集成的新型中性学目标编程方法在优化农业土地分配方面取得了重大进展.
  • 这种方法为管理不确定性和实现农业最佳经济结果提供了更强大的框架.
  • 这项研究强调了中性质优化和生物灵感计算在农业管理和决策中的实际应用的潜力.