逻辑斯蒂增长曲线模型的优选研究  

Positioning analysis of forged images based on bayesian model for fine-grained

作　　者：金涛[1] 

机构地区：[1]甘肃政法学院公安技术学院,甘肃兰州730070

出　　处：《中国建材科技》2015年第4期130-130,148,共2页China Building Materials Science & Technology

基　　金：甘肃政法学院校级重点科研项目(GZF2014XZDLW08);甘肃省通信产业咨询设计有限公司"通信产业咨询业务预测模型的优选研究"项目(201200081)

摘　　要：逻辑斯蒂增长曲线模型对于邮电规划预测业务是非常有用的模型,本文首先对逻辑斯蒂增长曲线模型可以线性化改造,利用最小二乘法原理简化公式,再结合0.618最佳选优方法优化模型,最小化残差平方和,较好完成的进行数据拟合。Logistic growth curve model for Telecom Planning prediction business is a very useful model. Firstly, this paper to the logistic growth curve model can be linearly transformed, using the principle of least square method simplified formula, combined with 0.618 optimum method optimization model, the residual sum of squares becomes minimum and the data can be fitted better.

关 键 词：逻辑斯蒂增长曲线模型 最小二乘法原理 0.618模型优化方法 

分 类 号：F201[经济管理—国民经济]