The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The paper combines rough sets and ANN to analyze inventory early-warning in supply chains. The introduction of Rough sets cuts down the input dimensions of ANN, and the ANN algorithm is improved by adding the momentum factor mc and applying adaptive learning rate. Lastly, according to the inventory data of a manufacturing enterprise in Handan City, the paper proves the validity of the proposed model.
According to the low sample and multifactor impact for long-medium term power load forecasting, the grey relational grade was used in screening factors, the combined model in BP neural network and SVM was established, and the multivariate variables and history load variables were used to roll prediction. The combined predictive values are obviously better than single method. Empirical study showed...
The paper proposes credit risk assessment model of commercial banks based on fuzzy probabilistic neural network model (FPNN) which combines the relative membership degree in fuzzy mathematics with Probabilistic Neural Network (PNN). The model makes up for a deficiency of ANN and BP arithmetic. Finally, an example is used to prove the calculation of this method is succinct rapid, and the evaluative...
The use of neural networks (NNs) for financial applications is quite common because of their excellent performances of treating non-linear data with self-learning capability. Often arises the problem of a black-box approach,i.e. after having trained neural networks for a particular problem, it is almost impossible to analyse them for how they work. The Fuzzy Neural Networks(FNN) allow to add rules...
To the loan offers, credit risk evaluation is the decisive link for investment. In order to evaluate credit of construction enterprises more scientifically and comprehensively, this paper establishes a systematic evaluation system, in which indexes, such as comprehensive loans status, qualities of leaders, third-party guarantee, have received due attention, and peculiar characteristics of the construction...
The stable prices rose in the real estate market attracted a large amount of funds injected into it, to choose a good investment environment has been a keyto get profit from investment. In this paper, a Support Vector Machine (SVM) model is founded to do the evaluation. Based on the comprehensive evaluation index system of real estate investment environment, Rough set (RS) is introduced to reduce...
With the development of electricity market reformation in China, it is especially important to evaluate the competition competence of power generating enterprises. Based on the characteristics of their, this paper bring forwards an index system to evaluate the competition competence of power generating enterprises. SVMs are widely used in load forecasting and bioinformatics systems. Conventional methods...
Because the traditional person-post fit method which considers person as the auxiliary to post becomes more and more unable to meet the need of modern enterprise management, competency model which is called the new basic point of human resource management was introduced into research on person-post fit. On the basis of consulting a lot of relevant reference and investigating of enterprise, it was...
With the continuous deepening of the power system reform and the blackouts of someplace on the world, the safety of the power grid has received high attention from all sections of the society. The former researches on the power grid safety are mostly about special parts, the method to estimate the whole power grid safety should be improved in the future. In this paper, according to the characters...
The paper adopts rough set reduction algorithm to reduce the influence factors of power plant selection and eliminate the uncorrelated attribution, through which we can obtain typical samples. After this, adopting fuzzy method to calculate the membership degree of the typical samples, which are looked on as the input of BP Neural Network and the expert values are as the expected output to train the...
This paper is to introduce a model. In the analysis of contract risk recognition, redundant variables in the samples spoil the performance of the SVM classifier and reduce the recognition accuracy. On the other hand, we usually canpsilat label one risk as absolutely good, or absolutely bad. In order to solve the problems mentioned above, this paper used rough sets (RS) as a preprocessor of SVM to...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.