本文選題：文化算法　切入點(diǎn)：微分進(jìn)化算法　出處：《西安工程大學(xué)》2012年碩士論文　論文類型：學(xué)位論文

【摘要】：目前，由于科學(xué)技術(shù)的相互交叉和滲透，單純的依靠一個(gè)領(lǐng)域的理論和方法已經(jīng)不能解決一些課題了，因此研究者開始把一個(gè)領(lǐng)域的研究成果運(yùn)用到另一個(gè)領(lǐng)域中，逐漸的多個(gè)領(lǐng)域交叉發(fā)展的結(jié)果形成了許多邊緣科學(xué)。文化算法作為一種新的進(jìn)化算法，它是通過對(duì)以往進(jìn)化理論的優(yōu)勢(shì)與缺陷進(jìn)行細(xì)致的分析后，同時(shí)參照社會(huì)進(jìn)化理論與已有的科研成果而提出的。文化算法是一種基于知識(shí)的雙層進(jìn)化系統(tǒng)，包括兩個(gè)進(jìn)化空間：一個(gè)是類似于其它進(jìn)化算法的種群空間，包含著進(jìn)化過程中的具體個(gè)體，另一個(gè)是信度空間，它是由進(jìn)化過程中獲取的經(jīng)驗(yàn)知識(shí)組成的。文化算法通過將種群知識(shí)與已有的一些智能算法有機(jī)的結(jié)合起來，可以提高算法整體的性能。文化算法本質(zhì)上是一種優(yōu)化算法，可以應(yīng)用于機(jī)器學(xué)習(xí)、網(wǎng)絡(luò)安全性、優(yōu)化設(shè)計(jì)、自動(dòng)控制、模式識(shí)別和經(jīng)濟(jì)學(xué)等廣泛領(lǐng)域。本文主要研究文化算法在經(jīng)濟(jì)學(xué)投資組合理論中的應(yīng)用。 本文先對(duì)文化算法的發(fā)展及現(xiàn)代投資理論的發(fā)展歷程進(jìn)行了闡述，隨后又進(jìn)行了以下的研究： 首先，詳細(xì)敘述了文化算法的計(jì)算框架，以及框架中兩個(gè)空間（信度空間和種群空間）和各個(gè)功能函數(shù)（接受函數(shù)、影響函數(shù)和更新函數(shù)）的設(shè)計(jì)。隨后又簡(jiǎn)單介紹了微分進(jìn)化算法，包括算法的基本原理，各參數(shù)的設(shè)計(jì)，以及該算法的優(yōu)缺點(diǎn)。然后結(jié)合以上兩種算法的優(yōu)點(diǎn)，本文將微分進(jìn)化算法嵌入到文化算法框架中，得出了文化微分進(jìn)化算法。然后借助11個(gè)測(cè)試函數(shù)分別對(duì)文化微分進(jìn)化算法及另外兩種算法進(jìn)行了測(cè)試，并得出了滿意的結(jié)果。 其次，簡(jiǎn)單介紹了傳統(tǒng)投資組合理論的研究方法，分析了以往理論的不足之處，而后重點(diǎn)介紹了現(xiàn)代投資理論的標(biāo)志—馬柯維茨投資理論，詳述了該理論的基本思想，分析了組合投資可以降低整體風(fēng)險(xiǎn)的原理。 再次，本文創(chuàng)造性的把文化微分進(jìn)化算法應(yīng)用于投資組合問題中。主要以馬柯維茨投資組合理論為研究對(duì)象，構(gòu)造了有風(fēng)險(xiǎn)偏好的投資組合模型，得出了相應(yīng)的非線性規(guī)劃模型，進(jìn)而構(gòu)造出了求解該模型的文化微分進(jìn)化算法。然后應(yīng)用測(cè)試數(shù)據(jù)進(jìn)行仿真實(shí)驗(yàn)，結(jié)果表明文化微分進(jìn)化算法比文化算法能更有效且快速的解決此類問題，在此也證明了本文提出的文化微分進(jìn)化算法的有效性。 最后，，通過對(duì)深圳交易所所有A股在2010年度的交易狀況的分析，再運(yùn)用相關(guān)軟件及編程對(duì)數(shù)據(jù)進(jìn)行篩選及計(jì)算，最終選出比較符合投資組合模型要求的6只股票，并把這6只股票的相應(yīng)數(shù)據(jù)代入有風(fēng)險(xiǎn)偏好的投資組合模型。然后分別用文化微分進(jìn)化算法、文化算法和微分進(jìn)化算法求解該模型。實(shí)驗(yàn)結(jié)果表明，文化微分進(jìn)化算法較其它兩種算法能以更快的速度收斂到全局最優(yōu)解，并且具有良好的魯棒性，這也表現(xiàn)出了該算法在實(shí)際應(yīng)用中的高效性。然后借助得出的最優(yōu)投資比例，引入實(shí)例來進(jìn)行實(shí)際的投資，并與不采用馬柯維茨組合理論的投資結(jié)果進(jìn)行比較，結(jié)果不但表明馬柯維茨組合理論在投資活動(dòng)中的重要性，更證明了文化微分進(jìn)化算法良好的尋優(yōu)特性，因此把該算法應(yīng)用到經(jīng)濟(jì)投資領(lǐng)域中，可以為投資者做出更快捷且準(zhǔn)確的投資決策。
[Abstract]:At present, the intercross and penetration of science and technology, simply rely on the theory and method of a field has been unable to solve some problems, so the researchers began to research a field applied to another area, the results of a number of areas of cross development gradually formed a lot of edge culture science. Algorithm is a new evolutionary algorithm, which is based on detailed analysis of advantages and disadvantages of the previous evolutionary theory, social evolution theory and referring to the existing research results and put forward. The cultural algorithm is a kind of double evolution system based on knowledge, including two evolutionary space: a similar population space in other evolutionary algorithms, including specific individuals in the process of evolution, the other is the reliability of space, it is the experience of knowledge acquisition by the evolutionary process. The composition of culture algorithm group knowledge General and some combination of intelligent algorithm organically, can improve the overall performance of the algorithm. The culture algorithm is essentially a kind of optimization algorithm, can be used in machine learning, network security, optimization design, automatic control, pattern recognition and other fields of economics. This paper focuses on the application of portfolio theory in Economics culture algorithm in.
This paper first expounds the development of cultural algorithm and the development of modern investment theory, and then the following research is carried out.
First of all, described in detail the calculation of the cultural algorithm framework, and the framework of the two space (belief space and population space) and all function (acceptance function, influence function and update function) is designed. Then a simple differential evolution algorithm is introduced, including the basic principle of the algorithm, design parameters, advantages and disadvantages the advantages of the algorithm. Then combined with the above two algorithms, the differential evolution algorithm is embedded into the cultural algorithm framework, the cultural differential evolution algorithm. Then the cultural differential evolution algorithm and the other two algorithms were tested by 11 test functions, and obtained satisfactory results.
Secondly, this paper introduces the research methods of traditional portfolio theory, analyzes the shortcomings of previous theories, and then introduces the symbol of modern investment theory Markowitz investment theory, describes the basic ideas of the theory, analysis of portfolio investment can reduce the risk of the whole principle.
Again, this paper creatively put cultural differential evolution algorithm is applied to the portfolio problem. Mainly based on Markowitz portfolio theory as the research object, constructs the model of portfolio investment risk preference, the corresponding nonlinear programming model, and constructs the culture solution of differential evolution algorithm of the model. Then the application of test data the simulation experiment results show that, the cultural differential evolution algorithm can be more effective and fast algorithm to solve such problems than culture, this also proves the validity of the cultural differential evolution algorithm is proposed in this paper.
Finally, through the analysis of the Shenzhen stock exchange all A shares in the 2010 annual transaction status, and then use the relevant software and programming for data selection and calculation, and ultimately selected 6 stocks compared with the requirements of the portfolio model, and the corresponding data into the portfolio model of these 6 stocks are then risk appetite. With the cultural differential evolution algorithm, cultural algorithm and differential evolution algorithm to solve the model. The experimental results show that the cultural differential evolution algorithm is compared with the other two algorithms can converge to the global optimal solution speed faster, and has good robustness, which also show the efficiency of the algorithm in the practical application of the optimal. The proportion of investment and with the help of the introduction of examples to the actual investment, and using Markowitz portfolio theory and investment results were compared, results not only show that the combination of Ma Kewei Bates. The importance of theory in investment activities also proves the good characteristics of cultural differential evolution algorithm. Therefore, applying this algorithm to the field of economic investment, we can make faster and more accurate investment decisions for investors.

【學(xué)位授予單位】：西安工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F830.91;TP301.6

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