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二维核密度估计算法.以及最优化计算核宽度。
二维核密度估计算法.以及最优化计算核宽度。-bivarite kernel estimation
- 2022-11-23 21:35:08下载
- 积分:1
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BP算法C++的BP算法源程序 BP算法C++的BP算法源程序
BP算法C++的BP算法源程序 BP算法C++的BP算法源程序 -BP algorithm C BP algorithm source algorithm C BP BP algorithm source code
- 2023-04-28 20:35:03下载
- 积分:1
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遗传算法的源程序例子,对于初学者有很大帮助,建议多
遗传算法的源程序例子,对于初学者有很大帮助,建议多-Genetic algorithm source code examples are very helpful for beginners, the proposed multi-
- 2022-07-24 23:43:38下载
- 积分:1
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高人用C++写的ALOPEX(即模式提取算法)实现程序,程序相当精炼,值得大家研究!...
高人用C++写的ALOPEX(即模式提取算法)实现程序,程序相当精炼,值得大家研究!-expert C++ to write the ALOPEX (model extraction algorithm) procedures, procedures considerable refining, we should study!
- 2022-03-16 02:34:02下载
- 积分:1
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神经网络模拟正弦函数演示
神经网络模拟正弦函数演示-neural network simulation sine function demo
- 2022-07-17 10:14:50下载
- 积分:1
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With QoS constraint multicast routing problem is an NP
带有QoS约束的组播路由问题是一个NP完全问题,遗传模拟退火算法是遗传算法和模拟退火算法的一种融合,可以为这类问题提供一个解决方案-With QoS constraint multicast routing problem is an NP-complete problem, genetic simulated annealing algorithm is a genetic algorithm and simulated annealing algorithm as a fusion, you can provide for such a solution
- 2022-09-17 21:25:02下载
- 积分:1
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BP人工神经网络算法,用java代码实现,用scilab图像显示,案例是港口吞吐量的预测...
BP人工神经网络算法,用java代码实现,用scilab图像显示,案例是港口吞吐量的预测-BP artificial neural network algorithm, using java code, using scilab image display, case is the throughput of the port prediction
- 2022-05-29 04:03:00下载
- 积分:1
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基于MATLAB完成的神经网络源程序
大家
基于MATLAB完成的神经网络源程序
大家-Based on the MATLAB neural network to complete the U.S. source
- 2022-06-22 03:59:04下载
- 积分:1
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模式识别k_means聚类算法。
模式识别k_means聚类算法。-kmeans clutering algorithm for Pattern Recognition
- 2023-04-21 16:10:03下载
- 积分:1
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Statistical learning theory is based on a more solid theoretical basis, in order...
统计学习理论是建立在一套较坚实的理论基础之上的,为解决有限样本学习问题提供了
一个统一的框架。它能将很多现有方法纳入其中,有望帮助解决许多原来难以解决的问题(比
如神经网络结构及参数选择问题);同时。在这一理论基础上发展了一种新的通用学习方法:
支持向量机(Support Vector Machine,SVM)。它己表现出很多优秀的性能,并已经成为当
今机器学习领域的研究热点。-Statistical learning theory is based on a more solid theoretical basis, in order to solve the learning problems of limited samples provides a unified framework. It will be incorporated into many existing methods, which could help solve many of the original difficult to resolve problems (such as neural network structure and parameters selection) the same time. Developed on the basis of this theory, a new universal learning methods: support vector machine (Support Vector Machine, SVM). It has been shown a lot of excellent performance and has become the hotspot of machine learning research in the field.
- 2022-03-02 21:50:04下载
- 积分:1