基于神经网络的分类器设计及优化-计算机应用技术专业论文.docx

PAGE PAGE VI A neural network classification method of large-scale agricultural dataset is proposed. With the analysis of the traditional BP-Adaboost algorithm, combined with cloud computing platform, a BP-AdaBoost algorithm using MapReduce programming mode was proposed. The new mode operates on the Hadoop cluster, After the two comparison experiments on the Hadoop cluster，the practicality of this model is assured. It can not only deal with massive data, but also reduce the time complexity of algorithm, with a better linear speedup ratio and accuracy. A neural network classification system for agricultural data is developed. Based on the Matlab2012 (a) platform, the correctness and effectiveness of the proposed method is validated with programming to achieve the main function, and achieved good results. The research results have certain research value and practical significance for intensive study of classification theory and method in the field of agricultural data. The establishment of a more precise and effective agricultural data classifier promotes the development of digital and precise agriculture. Key words: Neural Network, MIV, Fruit Fly Optimization Algorithm, MapReduce, Hadoop 目 录 摘 要 I ABSTRACT II HYPERLINK \l _bookmark0 1 绪论 1 HYPERLINK \l _bookmark1 1.1 研究背景及意义 1 HYPERLINK \l _bookmark2 1.2 研究内容及论文结构 2 HYPERLINK \l _bookmark3 1.2.1 研究内容 2 HYPERLINK \l _bookmark4 1.2.2 论文结构 3 HYPERLINK \l _bookmark5 2 基于神经网络的分类理论 4 HYPERLINK \l _bookmark6 2.1 分类理论及实现过程 4 HYPERLINK \l _bookmark7 2.1.1 分类的定义 4 HYPERLINK \l _bookmark8 2.1.2 分类的实现过程 4 HYPERLINK \l _bookmark9 2.1.3 分类器的评价标准 5 HYPERLINK \l _bookmark10 2.1.4 几种主要的分类方法及特性 5 HYPERLINK \l _bookmark11 2.2 基于神经网络的分类理论 6 HYPERLINK \l _bookmark12 2.2.1 神经网络概述 6 HYPERLINK \l _bookmark13 2.2.2 神经网络分类方法 7 HYPERLINK \l _bookmark16 2.3 神经网络分类方法的改进及其现状 9 HYPERLINK \l _bookmark17 2.3.1 神经网络与智能算法 9 HYPERLINK \l _bookmark18 2.3.2 神经网络与云计算 10 HYPERLINK \l _bookmark19