参数学习 meaning in English
parameter learning
Examples
- On the basis of theoretic convergence analyses of a single - coefficient learning algorithm , a transposition rule is proposed , which is applied to the single - coefficient learning algorithm to gain quick convergence speed in the phase of coefficient learning
最后在单参数学习算法收敛性的分析基础上，提出一种变调整规则的单参数学习算法，加快参数学习速度。 - The lyapunov function is used to analyze the convergence of the general learning rule , and it is proved in theory that the general learning rule has the inherent factor which adjusts the coefficient values to gain the minimum error
通过理论推导，用李雅普诺夫函数分析和验证通用参数学习规则的学习收敛性，揭示参数学习算法朝最小误差方向调整参数的内在因素。 - We make some further study on some problems , such as the learing of structure and parameters of bayesian network , network estimate and so on , on the basis of which a kind of learning method of bayesian network based on the attribute relativity analyse is achieved
研究了贝叶斯网络的拓扑结构学习、参数学习和网络评估等问题，在此基础上设计实现了一种基于属性相关性分析的贝叶斯网络学习算法。 - In this paper , we study the trading model based on the project " the network market " , which was implemented by the chongqing electronic commerce inc and us . aiming at the shortage of trading model in " the network market " , we employ game theory and multi - criteria decision theory , introduce the matchmaking schema based on price and quantity into electronic commerce application , bring forward a market matchmaking trading model including five phases : market matchmaking , reinforce learning , biliteral negotiation , contract signing , contract executing . the main work and conclusion as follows : considering the behaviour of multi - buyers with multi - sellers , we realise a matchmaking model based on the price and quantity through double auction mechanism under discriminatory and non - discriminatory price situation , analyse the incentive compatibility and competitive equilibrium of the mechanism
主要研究成果如下:针对多个买家与多个卖家的交易行为,提出一种撮合交易模型?采用价格和数量作为撮合要素,以双重拍卖机制为撮合手段,重点研究均价和差价形式下的实现机制,并对其激励相容性和市场均衡进行理论分析?为增强市场效率,论文提出了一种针对双重拍卖的学习机制,它以三参数学习模型为基础进行改进,借助交易历史信息,实现交易代理的自我学习 - Based on the analysis of the methods for optimizing the fuzzy neural networks before , this paper has finished following works : 1 ) we proposed a learning algorithm based on tabu search for fuzzy neural networks based on the model of anfis proposed by jyh - shing roger jang . then used the system for one variable function ' s approximation . 2 ) based on the first research , we improved the tabu search algorithm for the purpose of approximating complex functions . 3 ) analysis the capabilities of tabu search , and discuss the approximation ability and generalization ability of the fuzzy neural networks system according to the compute results
本文在对以前的模糊神经网络参数学习算法进行分析的基础上，做了以下几个方面的工作： 1 )根据禁忌搜索算法的特点，在jyh - shingrogerjang提出的anfis模型的基础上，将禁忌搜索算法应用于模糊神经网络线性和非线性参数的学习上，并将该模型用于单变量函数的逼近； 2 )在第一阶段的基础上，对算法进行了改进，使改进后的算法能够适用于复杂的ii函数逼近问题; 3 )根据计算机仿真的结果，对禁忌搜索算法的性能进行了分析，并对该模糊神经系统的函数逼近能力和泛化能力进行了讨论。