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迁移学习的经典文章，大多为国际顶级会议论文
迁移学习的经典文章，大多为国际顶级会议论文-Transfer of learning classic articles, most of the international top-level Conference Papers
- 2022-05-11 01:39:40下载
- 积分：1
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According to the characteristics of particle swarm optimization, using vc wrote...
根据粒子群算法的特点，用vc写出了源程序，可以实现粒子群的优化-According to the characteristics of particle swarm optimization, using vc wrote source code, you can achieve the particle swarm optimization
- 2022-04-09 13:01:50下载
- 积分：1
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本文在VC++环境下用演化算法实现了非线性参数回归，实验结果表明，用此方法能够很好的实现非线性参数回归。...
本文在VC++环境下用演化算法实现了非线性参数回归，实验结果表明，用此方法能够很好的实现非线性参数回归。-paper in VC environment using an evolutionary algorithm to achieve the nonlinear regression, experimental results indicate that this method can achieve good nonlinear regression.
- 2022-03-16 22:32:53下载
- 积分：1
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新的神经网络算法源程序，很适合初学者，也可以在上面进行改进！...
新的神经网络算法源程序，很适合初学者，也可以在上面进行改进！-New neural network algorithm source code, it is suitable for beginners, you can make improvements in the above!
- 2022-07-07 16:18:58下载
- 积分：1
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- 2023-03-08 03:25:03下载
- 积分：1
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BP神经网络预测
BP神经网络预测-BP neural network prediction
- 2022-01-25 21:19:01下载
- 积分：1
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C neural network development kits 8am, the C language can be used to develop a v...
C++神经网络开发包ANNIE，可以用C++语言开发各种神经网络：如BP，RBF，HOPFIELD等，同时随附件带有基于VC和.NET环境的示例源程序 -C neural network development kits 8am, the C language can be used to develop a variety of neural networks : as BP, RBF, Hopfield, along with the annex and with VC.NET environment example source
- 2022-03-26 05:06:39下载
- 积分：1
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- 2022-01-28 01:10:18下载
- 积分：1
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研究机器人控制不可多得资料，强烈推荐
研究机器人控制不可多得资料，强烈推荐-robot control study rare, strongly recommended!
- 2022-02-20 03:52:01下载
- 积分：1
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以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性...
以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性分类问题
为对象进行研究，仿真实验结果表明采用新保角映射可以快速显著地改善分类器泛化性能，而且能大幅度地减少支持向量的数目。-Two novel conformal transformations were proposed based on the Riemannian geometry theory and S.Amari’sidea.And the kernel function was modified by the transformation in a data-dependent way.Our experimental results for theartificial nonlinear data set show that the generalization performance of support vector machines classifier is improvedremarkably and the number of support vectors is decreased greatly.
- 2022-01-26 07:39:35下载
- 积分：1
