The average medical cost for each time and the frequency of hospitalization are expressed by countable fuzzy cardinal numbers according to the different health state. In this paper, we use addition, multiplication and...
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ISBN:
(纸本)9783642148798
The average medical cost for each time and the frequency of hospitalization are expressed by countable fuzzy cardinal numbers according to the different health state. In this paper, we use addition, multiplication and algorithms of countable fuzzy cardinal number to simulate and analyze the total amount of medical insurance claims. The result of the simulation and analysis is dynamic. It provides a new thought and method of calculating the total amount of medical insurance claims, and also provides a new way for risk management and control of the health insurance industry.
Micro-seismic monitoring as a regional monitoring means to predict important dynamic disaster of the mine, meanwhile, micro-seismic signal with abundant components of spectrum and frequency bandwidth characteristics. ...
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ISBN:
(纸本)9783642148798
Micro-seismic monitoring as a regional monitoring means to predict important dynamic disaster of the mine, meanwhile, micro-seismic signal with abundant components of spectrum and frequency bandwidth characteristics. Obtain sudden change time of micro-seismic abnormal signal and frequency components corresponding to sudden change time are the key issues in micro-seismic monitoring which to be solved urgently. In view of the variable precision rough set can not identify random rule which is supported by only a few examples, study a new hybrid model which combines rough set with Bayesian probability. In order to get more general and more reliable classification rule, make full use of intrinsic characteristic of micro-seismic monitoring knowledge system, more powerful in coping with noise data, derive a reliable and simple classification rule, it is more efficient to analyze a large number of micro-seismic data.
Fuzzy comprehensive evaluation has been widely used, and the method of moderate analysis is viewed as a better method. Through analyzing and studying the fuzzy comprehensive evaluation from different angles, this pape...
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ISBN:
(纸本)9783642148798
Fuzzy comprehensive evaluation has been widely used, and the method of moderate analysis is viewed as a better method. Through analyzing and studying the fuzzy comprehensive evaluation from different angles, this paper proposes two revised moderate analysis models -power function model and trigonometric function model. These two models are easy to understand, have better validity and the rationality, and have a further referential effect on doing research on fuzzy comprehensive evaluation.
A prediction method that based on combing principal component analysis and support vector machine is proposed. Principal component analysis was used to select input variable. The prediction model considers all-sided i...
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ISBN:
(纸本)9783642148798
A prediction method that based on combing principal component analysis and support vector machine is proposed. Principal component analysis was used to select input variable. The prediction model considers all-sided influencing factors and avoids the low precision and slow training induced by over-input. The example shows that it eliminates the relevance among factors, reduces the input variables and improves the accuracy and efficiency.
Fuzzy entropy, similarity measure and distance measure are three important measures of intuitionistic fuzzy sets. Their relationships are studied in this paper through operations between intuitionistic fuzzy sets, and...
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ISBN:
(纸本)9783642148798
Fuzzy entropy, similarity measure and distance measure are three important measures of intuitionistic fuzzy sets. Their relationships are studied in this paper through operations between intuitionistic fuzzy sets, and some formulas are given to transform a measure into another. Additionally, some examples are presented to show how to use the formulas above.
This paper discusses the completion of L -fuzzy topological vector spaces given by Fang and Yan [1] in 1997. We characterize the completable of L - fuzzy topological space and show that the corresponding completion is...
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ISBN:
(纸本)9783642148798
This paper discusses the completion of L -fuzzy topological vector spaces given by Fang and Yan [1] in 1997. We characterize the completable of L - fuzzy topological space and show that the corresponding completion is uniquely determined up to fuzzy order-hemomorphism.
In view of the complexity of actual decision-making problem and the cognitive fuzziness of decision-makers, we present a modified fuzzy-ISM based on 2-tuple linguistic representation information processing technology ...
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ISBN:
(纸本)9783642148798
In view of the complexity of actual decision-making problem and the cognitive fuzziness of decision-makers, we present a modified fuzzy-ISM based on 2-tuple linguistic representation information processing technology in this paper. Using TAM operator, we process 2-tuple semantic information of decision-making. After integration and standardization, we built the 2-tuple linguistic representation fuzzy interpretive structural model (2TLR-FISM). This model is more accurate for processing fuzzy semantic information than conventional ISM which may process semantic information rough and is easy to make distortion and loss of information. Finally, take a case study of analysing the influential factors of emergency management to illustrate the feasibility of the method.
The different concrete mixture of the self-compaction concrete concluded fly ash has great effect to the compression strength. In order to predict the compression strength of the self-compaction concrete concluded fly...
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ISBN:
(纸本)9783642148798
The different concrete mixture of the self-compaction concrete concluded fly ash has great effect to the compression strength. In order to predict the compression strength of the self-compaction concrete concluded fly ash, the article adopt BP Neural Network to train the system. It shows the hiding neural node is close to precision and it is possible for prediction of the self-compaction concrete with BP network.
A successive partial cluster algorithm for large data sets is proposed in tins paper. In each iteration of this algorithm, only a new cluster is generated by successive iteration method. Firstly, typical point was sel...
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ISBN:
(纸本)9783642148798
A successive partial cluster algorithm for large data sets is proposed in tins paper. In each iteration of this algorithm, only a new cluster is generated by successive iteration method. Firstly, typical point was selected successively based on sampling density and then cluster is constructed by using this typical point as seed. When the first cluster is produced, those data items contained by this cluster are deleted timely. Repeat this process until the remaining data set is small enough to read into memory. The rest of the data items are assigned to the nearest cluster respectively. The effective of this algorithm is verified by several experiments.
Starting from analyzing dynamic characteristics of the general energy system, this article discusses the mathematical mechanism of the GM (1, 1) model for producing AGO/IAGO data and the mathematical mechanism for con...
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ISBN:
(纸本)9783642148798
Starting from analyzing dynamic characteristics of the general energy system, this article discusses the mathematical mechanism of the GM (1, 1) model for producing AGO/IAGO data and the mathematical mechanism for constructing "the model equation" and the mathematical mechanism for parameter estimation. It also discusses other aspects of the application of the GM (1, 1) model. It points out: A. the classic GM (1, 1) model follows the principle of RMI model, but there exist background defects of the "planning predictions" and internal discords of the model caused by the prior assumptions in which both development coefficient and gray effective amount are constant, which restricts the application of the model. B. The classic GM (1, 1) model, in principle, only applies to fitting modeling of time sequences which tend to be slow and with wider intervals and positive stable values. C. Gray differential equation as a tool for estimating the parameters is not indispensible, so this article suggests optimizing parameter calculation method: gray differential equation providing initial iteration, using the end of AGO generating sequence as the boundary condition, etc. to improve the precision and explicability of the GM (1, 1) model.
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