园林工程技术论文提纲

论文题目：阿联酋某公司园林工程项目质量管理研究

摘要：随着全球经济的发展,生态环境问题越来越引起各国政府的重视,在各国城市规划建设过程中,城市园林设计是其重要的组成部分,城市园林设计是否合理直接关乎城市是否宜居,进而影响到人们的生活幸福度。经过金融危机的洗礼,阿拉伯联合酋长国（以下简称阿联酋）力求摆脱化石能源产业为主的单一经济,加速向可持续发展的多元化经济转型,随着政府加大基础设施建设投资政策的出台,阿联酋工程项目市场呈现了巨大的发展潜力。与此同时,我国也十分重视城市园林建设,为加强阿联酋绿色文明建设,政府通过制定引导性政策等不断提高绿色生态文明在国家发展中的地位以及目标。园林工程作为绿色生态文明建设的重要一环,是一个城市的重要基础设施,是市民活动感受生态文明建设的活动中心,同时也是一个城市发展水平的表现。阿联酋政府为了可持续发展,特别是在园林城市、森林城市方面建设做出了非常多的努力。但是阿联酋在大量的城市园林工程建设中,各种工程问题都被集中暴露,管理的粗放,建设资源的浪费,效率低下等。基于上述背景,本文充分阅读相关文献和相关案例,把改进型的神经网络技术引入质量管理,构建了一款基于神经网络的阿联酋园林工程项目质量管理系统,本系统工程施工质量和项目管理质量两个方面进行神经网络样本训练,结合数据挖掘算法并通过样本训练确定施工管理、质量管理、进度管理等要素的权重,从而得出园林工程项目质量的关键要素,进而为阿联酋园林工程建设提供借鉴,为阿联酋园林工程建设的健康发展,践行绿色生态文明建设具有一定的借鉴和参考作用。

关键词：园林工程;项目管理;质量管理;神经网络算法

学科专业：管理科学与工程

摘要

Abstract

Ⅰ Introduction

1.1 Research background and research significance

1.1.1 Research background

1.1.2 Research significance

1.2 Related theoretical research

1.2.1 Overview of landscape engineering

1.2.2 Quality management of landscape engineering projects

1.2.3 Principles of garden construction quality management

1.2.4 Procedures for quality management of landscape engineering construction

1.2.5 Basic theory of neural networks

1.2.6 Relevant Theories on BP Neural Network Model

1.2.7 Feasibility of neural network applied to engineering quality

1.2.8 Structure and working methods of neural networks

1.3 Research content methods and framework

1.3.1 Research content

1.3.2 Research methods and framework

Ⅱ Status Quo of Quality Management of Landscape Engineering Projects of a Company in the United Arab Emirates

2.1 Overview of UAE Country

2.2 The main features of the UAE project

2.2.1 Characteristics of religious folk customs for project construction

2.2.2 Features of architectural design and implementation

2.2.3 Features of building materials machinery

2.3 Analysis of quality management of landscape engineering in UAE

2.3.1 Problems with current construction quality management

2.3.2 Analysis of the causes of the current construction quality management

2.4 Analysis of quality influencing factors in construction phase of garden engineering

2.4.1 Construction personnel

2.4.2 Raw materials

2.4.3 Mechanical equipment

2.4.4 Construction method

2.4.5 Construction Environment

Ⅲ Design of Quality Management Improvement Plan for a Garden Engineering Project of a Company in the United Arab Emirates

3.1 Set engineering quality factors as control points

3.1.1 Determination of engineering quality control points

3.2 Design of quality control model based on neural network

3.2.1 Determination and processing of neural network model data

3.2.2 Principles for selecting initial weights of network models

3.2.3 Determination of the number of input and output nodes

3.2.4 Determination of hidden layer nodes

3.2.5 Determination of correlation function

3.3 Improved countermeasures

Ⅳ Application of Quality Control Model of a company in the UAE Garden Project

4.1 Selection of sample data for engineering cases

4.1.1 Selection principles of samples

4.1.2 Processing of sample data

4.2 Training and simulation of neural network models

4.2.1 Training of neural network models

4.2.2 Simulation of neural network to engineering quality

4.3 Analysis of model validation results

4.3.1 Accuracy analysis of verification results

4.3.2 Analysis of weights of influencing factors

Ⅴ Implementation and guarantee of quality management for garden engineering projects of a company in the United Arab Emirates

5.1 Guarantee of garden construction quality system

5.2 On-site quality management planning

5.2.1 Establishing an on-site organization

5.2.2 Establish a standardized management system

5.3 Specification of on-site construction quality management

5.3.1 Improve the quality awareness of construction workers and ensure construction quality

5.3.2 Strictly control the quality of construction equipment and onstruction materials

5.4 Late maintenance management of landscaping projects

5.5 Establish a quality management mechanism for “continuous improvement” ..

Ⅵ Conclusion

6.1 Conclusions

6.2 Research prospects

References

Acknowledgement