Kun-Li Wen

The Development of Completed Grey Relational Grade Toolbox via Matlab

The software in engineering field, even in others filed become most important and more necessary in the 21 century, although there are many toolbox, such as fuzzy, chaos, ..., etc., had been developed in the past, the grey toolbox still seldom and not quite completed. Therefore, in this paper, the focus is on the toolbox development of ordinal grey relational grade and cardinal grey relational grade by using Matlab to development the completed grey relational grade toolbox. Firstly, we preview the whole mathematical foundation of grey relational grade in detail. Secondly, the mathematics model of ten kinds of grey relational grade, and two types of grey relational grades (ordinal and cardinal) are presented. Thirdly, based on the mathematics model, we use Matlab to develop the grey relational grade toolbox. As the results, in this paper, ten kinds of grey relational grade methods, and two types of grey relational grades (ordinal and cardinal) are developed, we can say this kind of completed research is the main contribution and is the first research in grey relational grade. Also can extends in the economy in benefit, for our research, the market price of the whole grey relational grade toolbox with our evaluation; at least will over US 500 dollars. To sum up, we hope this completed grey relational grade toolbox is not only to enhance the depth research of grey relation grade, buy also become a new approach for the applications in grey system theory

The development of Grey Verhulst toolbox and the analysis of population saturation state in Taiwan-Fukien

The principle of population prediction is one of the most important policies for developing countries, and population numbers are a basis for the formula used by the government with very limited resources. If the population increases significantly, or growth is reversed, then the entire balance of the ecology is seriously affected. The article initially focuses on the use of the Grey Verhulst method trying to construct saturation numbers for the population. A toolbox is also developed to provide a very convenient way of generating a great numerical analysis of a real case. Finally, an example is given to predict saturation numbers of the population numbers in Taiwan-Fukien, and the results tell us it will not exceed 23 million. Based on the above methods, the full results not only provide the saturation numbers, but also can become the reference making policy for the best layout of the population source.

The Weighting Analysis of Influence Factors in Gas Breakdown via Rough Set and GM(h,N)

In power system filed, to study the characteristics of the gas breakdown is essential and of importance in designing the protection of high voltage system as well as to the power system reliability. Hence, in this paper, the major purpose is to propose a refined mathematical approach based on core finding in rough set method and GM(h,N) method in grey system theory to find the priority of influence factor in gas breakdown. And also created rough set and GM(h,N) toolbox based on Matlab, which to help the complex calculation and analysis. As the result, we not only can get the rank of influence factor in gas breakdown, but also provides a new idea for extension the applications of rough set and GM(h,N) method.

The evaluation of liver function via grey relational analysis

Liver diseases and liver cancer has been the top ten causes of death among ten leading causes of death in Taiwan and always in the top. Usually, in the general liver function examination, biochemical test is the most common and a test that show the most direct reflection of the body condition. The health subject can determine the further inspection according to the inspection results. Nevertheless, the result of biochemical tests is not absolute, nor is the results represent in the normal range will not be suffering from liver disease. Therefore, how to let the health subject understand his/her own health condition is the main purpose of this paper. So, this paper makes use of grey relational analysis method and according to the standard values of hospital test results to be divided into Level method and compare with the health subjects test results. It will convert the past ordinal decision into cardinal quantitative evaluation value and evaluate liver functions level. At the same time, it develops MATLAB GUI toolbox to assist the numerical calculation, which can complete a medical assistance platform for liver function evaluation. It not only provides a further step of making decision for doctors in order to promote medical quality, but also provides a new research direction of this field.

Applied GM(0,N) Model in the Study of Influence Factor in Preterm Neonates

The aim of this study is based on GM(0,N) model to evaluate the biochemical factors in preterm neonates, include growth hormone (GH), insulin-like growth factors (IGFs), IGF-binding proteins (IGFBPs) and leptin, the proteins known to be involved in the regulation of growth. And find the influence for each factor corresponding with the body mass index(BMI) and postnatal growth(PI). First, we use the measurement data from blood sample, which collected from 55 preterm neonates for four continuous weeks as our original data. Second, The GM(0,N) model in grey system theory is applied as our mathematics model, to rank the influence from our original data, and we also create a toolbox, which via Matlab to help our calculation. After the results are found, we find that the results are quite matching with the traditional method. Hence, we not only can get the rank of influence in preterm neonates by grey system method, but also provide the new direction in this kind of research.

Apply rough set and GM(h,N) model to analyze the influence factor in gas breakdown

In power system field, to study the characteristics of the gas breakdown is essential and of importance in designing the protection of high voltage system as well as to the power system reliability. Hence, in this paper, the major purpose is to propose a refined mathematical approach based on rough set method and GM(h,N) method to find the priority of influence factor in gas breakdown. And also created rough set and GM(h,N) toolbox based on Matlab, which to help the complex calculation and analysis. As the result, we not only can get the rank of influence factor in gas breakdown, but also provides a new idea for extension the applications of rough set and GM(h,N) method.

The Development of Grey Generating Toolbox Based on Matlab

For any system in the real world, it is known that the original data is always random. Therefore, before it can be operational, the data must be retreated; otherwise, there may be errors in the results. In grey system theory, it contains a large amount of data and complex mathematical operation; the application software design of grey system theory in the past was written individually. Though this way could solve the problem for the moment, it is not very sufficient for the generating in using the scope of the aspect. In this paper, we develop the whole grey generating model toolbox in grey system theory, to cooperate with the study and application of in real system. Based on the above-mentioned reasons, we present four grey generating methods. By adopting Matlab, we create the idea of computer toolbox for grey system theory. As the results, in this paper, four kinds of grey generating methods are developed, we can say this completed research could be one of the main contributions and is the first research in grey generating. For our research, we get several important results: This completed grey generating toolbox to enhance the depth research of grey system; In addition to reduce time of analyzing and promote the analyzing level; Guide the grey system theory to the internationalization and reach the research of academy to promote the teaching.

The Development of GM (1,1) Error Toolbox Based on C Language

In the prediction research, the main purpose is to minimize the prediction error; however, the goals cannot be fulfilled completely. Even we choose GM (1,1) model, we also need to minimize the prediction error. Hence, in this paper, we first focus on the influence parameter α in GM (1,1) model, then, analyze the characteristics of α step by step. Second, we give up the α=0.5 method, and use numerical method to find the prediction error corresponding with α value and plot the figure of the function of error. Third, for massive data testing, they show that the minimum prediction error does not occur at α=0.5, even not nearly by α=0.5. Fourth, the average prediction error for which the Class Ratio test are fail is sufficient larger than the average prediction error for which the Class Ratio test pass. Finally, after the mathematics model has been presented; we also develop a toolbox, which based on C language to assist us to implement our approach. Consequently, we conclude that the value of α is adaptive in the interval of [0,1] in GM (1,1) model.

Using GM(1, 1) Meshsmooth Model to Construct Secure Network Communication System

In this paper, we combined the public key cryptograph system proposed by Diffie and Hellman, with the infinite generation keys based on GM(1, 1) model , which in grey system theory, to establish the GM(1, 1) meshsmooth model to construct secure network communication system. The whole mathematics concept is used finite original code to create an infinite variables code sequence, and got the code from the known secrete key. In this paper, we define two parameters: cryptography sequence ψ and 3(superscript rd) order symmetric group S3 and presented six cryptography models to contribute our system. According to the implement of real case, the secrete value is high to O(The equation is abbreviated) for public system, and it is hard to calculate the code sequence by the present computing ability. Therefore, to break into this system by mathematical formula is no way nowadays. Besides, to promote the efficiency, we also develop a toolbox, it can not only to decrease the calculation time, but also examine the reliability of our system.

Appling grey relational analysis and rough set method to analyze the weighting of influence factor in early childhood education

Early childhood education is much more important in our society. It is difficult to pick a good school because now parents have more choices, especially because there are schools all over Taiwan. In past research, we cannot find a direct method that helped parents choose quality school. Hence, the main purpose of this study is to analyze the influence factor for kindergarten, and give suggestions for parents on the more effective way to pick a quality school. In this paper, we use the grey relational grade in grey system theory and significant in rough set theory as the mathematics models. Through the practical analysis in Taichung area, this study reveals that the most important factor is the ratio of students to teachers; it is quite matching with the real thinking of parents, and then parents could take the study result for the reference as making choices in kindergarten.