| 摘 要: 本文重点探讨深度计算评估模型的算法设计原理，从模型构建与程序开发两方面做出研究，结合大数据 学习特征，探讨计算评估模型建立的主体方向。并以具体算法应用为例，对设计构建内容进行整理，帮助提升大数据环 境下的信息资源更新获取效率，为深度计算评估模型算法应用提供技术参照。 |
| 关键词: 大数据特征学习；深度计算；评估模型 |
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中图分类号: TP301
文献标识码: A
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| 基金项目: 广东省教育厅高校特色创新类项目(自然科学)(2017GKTSCX110). |
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| Design and Research of the Algorithm for Depth Computation Evaluation Models Based on Big Data Feature Learning |
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TANG Xinyu,CHEN Xiaoming1,2
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1.( 1.Department of Computer Application Technology, Guangdong College of Business and Technology, Zhaoqing 526040, China;2.
2.Zhaoqing Agricultural School, Information Centre, Zhaoqing 526040, China)
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| Abstract: This paper focuses on the algorithm design principle of the depth computation and evaluation model,and studies the establishment of the computation evaluation model and program development,and discusses the main direction of the establishment of the depth computation evaluation model combining with big data feature learning.Taking the application of the specific algorithm as an example,the paper explores the content of design and construction,and helps improve the efficiency of parameter acquisition in the big data environment. |
| Keywords: big data feature learning;depth computation;evaluation model |
