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Journal of Zhejiang University SCIENCE A

ISSN 1673-565X(Print), 1862-1775(Online), Monthly

Mechanism of the insecticidal effect of lambda-cyhalothrin loaded mesoporous silica nanoparticles with different sizes and surface modifications on Ostrinia furnacalis (Guenée) larvae

Abstract: Toxicity regression equations and half lethal doses (LD50) of LCNS treatment of O. furnacalis larvae at 24, 48, and 72 h are shown in Table 1. The LD50 of LCNS (dissolved in phosphate buffered saline (PBS) solution containing 1% acetonitrile, pH=7.0) at 24, 48, and 72 h was 341.7, 112.1, and 16.3 mg/kg, respectively. These values were used as the toxic dose reference of drug-loaded nanoparticles. Our previous study suggested that increasing the LCNS dose from 10 to 400 mg/kg increased the mortality rate of free LCNS from 25% to 65%; a low dose of M4/L (10 mg/kg) resulted in a higher mortality rate (70%) at 24 h (Xiao et al., 2022). Considering the easy photolysis of LCNS (Xiao et al., 2022), insecticidal experiments using 10 or 200 mg/kg LCNS or M4/L in the diet of the O. furnacalis larvae with 12-h starvation were conducted under dark or light conditions to analyze the effect of light on larval mortality.

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Chinese Summary  <422> 一种改进的和声搜索算法及其在权重模糊产生式规则获取中的应用

叶绍强1,周恺卿1,Azlan Mohd ZAIN2,王方岭1,Yusliza YUSOFF2
1吉首大学通信与电子工程学院,中国吉首市,416000
2马来西亚理工大学信息处理技术学院,马来西亚柔佛州士姑来, 81310
摘要:和声搜索算法(harmony search, HS)是一种随机元启发式算法,其灵感来自于音乐家的即兴创作过程。针对HS在求解中易陷入局部极值等不足,本文提出一种混合布谷鸟算子的改进的和声布谷鸟搜索算法(modified HS withahybridcuckoosearch (CS) operator, HS-CS)增强全局搜索能力。该算法首先对HS音高扰动调整方法的随机性进行分析,根据和声库中解的质量生成自适应惯性权重,并重构微调带宽寻优,提升HS的寻优效率及精度。其次,引入CS算子扩大解空间的搜索范围和提高种群密度,从而能够在随机生成和声和更新阶段快速跳出局部极值。最后,构建动态参数调整机制以提高算法寻优的效率。通过证明3个定理揭示HS-CS是一种全局收敛的元启发式算法。在实验部分,选取12种经典的测试函数优化求解以验证HS-CS算法的性能。数值分析结果表明,HS-CS在处理高维函数优化问题上显著优于其他算法,表现出较强鲁棒性、高收敛速度以及收敛精度。为进一步验证算法在实际问题求解中的有效性,将HS-CS用于优化BP神经网络进行加权模糊产生式的规则抽取。仿真实验结果表明,HS-CS优化后的BP神经网络能够获得较高的规则分类精度。因此,从理论和应用方面都证明了HS-CS是行之有效的。

关键词组:和声搜索算法;布谷鸟搜索算法;全局收敛;函数优化;权重模糊产生式规则抽取


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DOI:

10.1631/jzus.A2200334

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On-line Access:

2023-04-25

Received:

2022-07-02

Revision Accepted:

2022-11-17

Crosschecked:

2023-04-25

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