本文選題：BP神經網絡 + 服務發(fā)展　； 參考：《北京中醫(yī)藥大學》2017年碩士論文

【摘要】：目的:通過文獻梳理北京市社區(qū)中醫(yī)藥服務發(fā)展中的問題,結合社區(qū)中醫(yī)藥相關政策,多角度構建社區(qū)中醫(yī)藥服務發(fā)展影響因素初步框架。運用BP神經網絡方法建立社區(qū)中醫(yī)藥服務發(fā)展影響因素分析模型,計算北京市社區(qū)中醫(yī)藥服務發(fā)展影響因素指標權重,分析北京市社區(qū)中醫(yī)藥服務發(fā)展中的主要影響因素,探討該方法在影響因素分析中的優(yōu)勢。方法:1、文獻研究法。收集CNKI,萬方,維普等數(shù)據庫中基層中醫(yī)藥文獻,歸納2005年至2016年社區(qū)中醫(yī)藥服務發(fā)展現(xiàn)狀及存在的問題。2、問卷調查法。以函調和現(xiàn)場調研方式,收集北京市64家社區(qū)衛(wèi)生服務中心中醫(yī)藥服務數(shù)據。3、BP神經網絡分析。本研究采用BP神經網絡方法分析北京市社區(qū)中醫(yī)藥服務發(fā)展影響因素權重。利用matlab 2010b軟件,構架以北京市社區(qū)中醫(yī)藥服務發(fā)展影響因素為輸入變量,社區(qū)中醫(yī)藥服務發(fā)展效率為輸出變量的三層網絡模型,通過相關公式轉化成社區(qū)中醫(yī)藥服務發(fā)展影響因素權重值。4、DEA分析。運用超效率CCR模型,測算社區(qū)中醫(yī)藥服務發(fā)展效率,將社區(qū)中醫(yī)藥發(fā)展效率作為BP神經網絡模型輸出變量。5、頻數(shù)統(tǒng)計分析。對基本情況、人員、服務中部分指標和制約因素采取頻數(shù)統(tǒng)計方法進行分析,為本研究建議的提出提供數(shù)據支持。結果:本研究建立了以社區(qū)中醫(yī)藥服務發(fā)展影響因素指標為輸入節(jié)點,以社區(qū)中醫(yī)藥服務發(fā)展效率為輸出節(jié)點,隱節(jié)點數(shù)為8個的三層神經網絡模型。其中,樣本數(shù)為64例,權重結果如下:中醫(yī)藥業(yè)務用房面積(0.0974),中藥飲片種類(0.1002),中醫(yī)藥設備種類(0.1118),中醫(yī)師數(shù)(0.1006),中級以上中醫(yī)師數(shù)(0.1376),中醫(yī)藥適宜技術種類(0.1250),新開展的中醫(yī)藥適宜技術種類(0.1174),重點人群中醫(yī)藥保健種類(0.0964),中醫(yī)藥慢病管理種類(0.1136)。結論:1、人員、技術是北京市社區(qū)中醫(yī)藥服務發(fā)展主要影響因素。北京市社區(qū)中醫(yī)藥影響因素權重值前四位的因素為中級以上中醫(yī)師數(shù)、中醫(yī)藥適宜技術種類、新開展的中醫(yī)藥適宜技術種類、中醫(yī)藥慢病管理種類。2、BP網絡是一種優(yōu)質的分析社區(qū)中醫(yī)藥服務發(fā)展影響因素的方法。在運用兩種方法構建社區(qū)中醫(yī)藥服務發(fā)展影響因素模型時,BP神經網絡模型R2值達到0.97左右,而多元線性回歸模型R2僅為0.1991,回歸模型各自變量P值大于0.05,模型沒有統(tǒng)計學意義。
[Abstract]:Objective: to analyze the problems in the development of community traditional Chinese medicine (TCM) services in Beijing, and to construct a preliminary framework of influencing factors for the development of community traditional Chinese medicine (TCM) from different angles.Using BP neural network method to establish the analysis model of influencing factors of community traditional Chinese medicine service development, to calculate the index weight of influencing factors of community traditional Chinese medicine service development in Beijing, and to analyze the main influencing factors in the development of community traditional Chinese medicine service in Beijing.The advantages of this method in the analysis of influencing factors are discussed.Methods: 1, literature research.The basic TCM documents in CNKI, Wanfang and Weipu databases were collected, and the status quo and existing problems of community TCM service development from 2005 to 2016 were summarized.The data of traditional Chinese medicine service in 64 community health service centers in Beijing were collected by correspondence and field investigation. BP neural network was used to analyze the data.In this study, BP neural network method was used to analyze the weight of factors influencing the development of community traditional Chinese medicine service in Beijing.By using matlab 2010b software, a three-layer network model with the factors influencing the development of community traditional Chinese medicine service in Beijing as input variable and the efficiency of community traditional Chinese medicine service development as output variable is constructed.The weight value of influencing factors of community traditional Chinese medicine service development was transformed into DEA analysis by relevant formulas.The development efficiency of community traditional Chinese medicine (TCM) service is calculated by using the super-efficiency CCR model. The development efficiency of community TCM is regarded as the output variable of BP neural network model .5. the frequency is statistically analyzed.The basic situation, personnel, some indicators and constraints in the service are analyzed by means of frequency statistics to provide data support for the proposal of this study.Results: in this study, a three-layer neural network model was established with the index of influencing factors of community TCM service development as the input node, the community TCM service development efficiency as the output node and the number of hidden nodes as 8 nodes.Among them, the sample size is 64,The weight results are as follows: the area of accommodation used in Chinese medicine business is 0.0974m, the type of Chinese medicine pieces is 0.1002U, the type of equipment of Chinese medicine is 0.1118m, the number of TCM doctors is 0.1006m, the number of doctors above intermediate level is 0.1376m, the category of suitable technology of traditional Chinese medicine is 0.1250m, the newly developed type of suitable technology of traditional Chinese medicine is 0.1174.The type of health care of Chinese medicine is 0.0964, and the type of management of chronic disease of traditional Chinese medicine is 0.1136.Conclusion 1, personnel and technology are the main influencing factors for the development of community traditional Chinese medicine service in Beijing.The first four factors of the weight value of the influencing factors of traditional Chinese medicine in Beijing community are the number of Chinese medicine doctors at or above the intermediate level, the types of appropriate techniques of traditional Chinese medicine, and the new types of suitable techniques of traditional Chinese medicine.BP network is a good method to analyze the influencing factors of community TCM service development.When two methods were used to construct the model of influencing factors of community TCM service development, the R2 value of BP neural network model was about 0.97, while that of multivariate linear regression model was only 0.1991.The regression model's variables P value was more than 0.05, and the model had no statistical significance.
【學位授予單位】：北京中醫(yī)藥大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R197.61

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