In the thesis, the basic principle, model, parameter estimation and information function of IRT are discussed based on three education test theories.
本文首先在介绍了三种教育测量理论的基础上，较详细地论述了项目反应理论的基本原理、模型、参数估计以及信息函数等。
In this paper, we present a new kind of combining forecasting model based on the generalized weighted functional mean and the parameter estimation methods of its weighting coefficients.
给出一种新的组合预测模型——广义加权函数平均组合预测模型及其加权系数的参数估计方法。
However, the parameter model based PSD estimation is used with the assumption that the model order is determined as low as possible through prior knowledge.
而功率谱估计中基于参数模型的方法得到广泛应用，但建模时通常只能根据经验选择一个固定较低的阶数。
In order to improve the forecast precision of modified GM (1, 1) model, a new parameter estimation formula based on accumulating method to modified GM (1, 1) model is proposed.
为了提高新息改进GM(1,1)模型的预测精度，引入累积法对新息改进GM(1,1)模型的参数进行估计，给出了新的参数估计公式。
Then it applies the method of parameter estimation based on the model of parameters-subsystem parameters function to the fault detection of servo system.
之后，应用基于模型参数-子系统参数关联方程的参数估计方法，对伺服系统进行故障诊断。
A novel method of the on line model parameter estimation based on NFI CMAC is designed. Numerical simulation has shown its feasibility and effectiveness.
基于NFI -CMAC，提出了一种快速、高精度的控制系统参数在线智能辨识方案，仿真实例表明了该方案的可行性与有效性。
The Maximum Entropy method is a kind of parameter spectrum estimation method based on ar model.
最大熵谱估计法是以AR模型为基础的一种参数谱估计方法。
Two Solutions to the model equivalent parameter estimation are proposed, one based on the three-phase short-circuit capacity, this method works with good computational speed, but accuracy is not high;
对该模型提出两种求解方法，一是基于三相短路容量思想的等值参数估计，计算速度快，但精度不高；
This new algorithm greatly raises the speed of parameter identification and computation convergence. An avionic equipment cost estimation model is set up based on ANFIS network.
混合学习算法提高了网络参数的辨识速度和网络计算的收敛速度。
This new algorithm greatly raises the speed of parameter identification and computation convergence. An avionic equipment cost estimation model is set up based on ANFIS network.
混合学习算法提高了网络参数的辨识速度和网络计算的收敛速度。
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