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An annotated survey of approaches to design optimization based on possibility theory and evidence theory is presented and prominent characteristics are described in this paper, especially addressing epistemic uncertainty for large-scale and complex systems when statistical data is scarce or incomplete. We first analyze the uncertainties encountered in design and the limitations of probabilistic approach...
The fuzzy c-means algorithm is a useful technique for clustering real s-dimensional data, but it can not be directly used for partially missing data sets. In this paper, the problem of missing data handling for fuzzy clustering is considered, and a statistical representation of missing attributes is proposed. The approach reduces the statistical analysis of missing attributes to the subsets of the...
The fuzzy and integrative methods can be used in translation quality evaluation. A statistic and quantitative method named FIEM (fuzzy integrated evaluation method) was introduced to evaluate two translated texts (target texts). The model of FIEM is composed by the element set, evaluation set, threshold vectors and evaluation matrix, which first two sets are both fuzzy. The results of case study and...
The paper focuses on the image segmentation methods based on histogram analysis, and proposes a novel image segmentation approach based on cloud model. Firstly, the paper introduces the basic principles of cloud model. Similar to type-2 fuzzy sets, cloud model considers the uncertainty of membership grades. But it also considers the randomness of them. It is a new kind of uncertain model which is...
Efficient performance measurement on reverse supply chain (RSC) is the basis of optimizing RSC. In view of the shortage and deficiency on performance measurement of RSC, in this paper, an integral performance measurement index system is designed based on balance score card (BSC) and RSC structure characteristics, including a set of finance, customer, internal business process, learning and developing...
On the basis of establishing the evaluation index system, the paper proposes fuzzy centralization statistical theory to evaluate the efficiency of firefighting & rescue command. Applying fuzzy centralization statistical theory, the random and fuzzy indexes in the efficiency evaluation index system are mathematically analyzed, and the total weights of all the indexes are calculated. The result...
There are many uncertainties which have the characteristics of high investment and high risk in coal-bed methane underbalanced drilling. If the potential risk and its state can be predicted in advance, the probability of risk occurrence will be reduced to the minimum extend. On the basis of risk identification of coal-bed methane underbalanced drilling, it concludes that the drilling risks mainly...
Most methods of structural states assessment focused on statistical analysis considering only random uncertainties, or on fuzzy recognition considering only fuzzy uncertainties. The cloud model considers both of the two, implementing the transform between qualitative evaluation and quantitative numerical value. In this paper, healthy observations are used to determine the expectation function and...
The stability evaluation of the central pillar between twin neighborhood tunnels is an important step in a tunnel construction process. In this paper an indicator system was proposed to evaluate the stability state of the central rock pillar between twin neighborhood tunnels; then an AHP (Analytic Hierarchy Process) model was constructed to calculate the weights of indicators; and finally, with fuzzy...
High-rise building has greater risk of fire according to its features such as great height, complex structure and diverse functions and so on. It's easy to cause heavy casualties and property losses once the high-rise building fire taking place. It's of great significance, through the fire-safety evaluation for high-rise building, to prevent the occurrence of high-rise building fire in time. For the...
It presents an approach based on ER models to solve statistical skew and low efficiency problems in multi-relational data mining. It makes use of the constraints between entity sets and relationship sets of an ER model, and applies extended SQL statistical primitives to produce multi-relational frequent patterns on the interesting attributes, avoiding physical joining among all relational tables....
Text Categorization (TC) is an important component in many information organization and information management tasks. In many TC applications, the case-base grows at a fast rate and this causes inefficiency in the case retrieval process. Using Case-Base Maintenance learning via the GC (Generalization Capability) algorithm, which can reduce the case number into KNN algorithm, can improve efficiency...
This paper studies discriminant modeling method of compositional data. By adopting logratio transformation of compositional data and then implementing Fisher discriminant modeling method to the transformed data, the logcontrast linear discriminant function of compositional data is derived. The model presents the following advantages: i) the transformed data, which is scaled up to a broader range of...
In order to solve the problem of feature extraction in the gear fault pattern recognition, a method of feature extraction based on atomic decomposition was proposed. Signals are rapidly decomposed using matching pursuit with the constructed Gabor dictionary. The frequency parameters and respective correlation values of the selected atoms constitute the feature vector of signal. Binary Tree Support...
Medical image segmentation has been a hot spot in recent years. And the segmentation of brain vessels image becomes a key-problem due to its complicated structure and small proportion. In this paper, the brain MRI images are processed with statistical analysis technology, and then the accuracy of segmentation is improved by the random assortment iteration .First the MIP algorithm is applied to decrease...
A research on the demodulation performance of second-order cyclic autocorrelation and spectral density function of the frequency modulated (FM) signals with cyclostationarity properties was done. A comprehensive analysis was made to interpret the spectrum domain slice map and the cyclic spectral domain slice map for the three-dimensional cycle spectral diagram of the original signal. Then the modulation...
The study of growth model is a basic research in forest growth and yield modeling. Most of growth models were developed using ordinary regression method. It is assumed that the observations were independent and obey Gauss distribution. Those models reflect the average growth across different plots, but neglect the correlation and variance between individuals and plots. However, mixed-effects models...
Discriminating photorealistic computer graphics from natural images is an important problem in image forensics. A new distinguishing method using second-order difference statistics is proposed in this paper. Firstly, the second-order difference signals and predicting error signals of both original and calibrated images are extracted in the HSV color space, and then the variance and kurtosis of second-order...
Moxibustion is one of treatment methods which are commonly used in clinical Chinese medicine, with several thousand years of history. However, many factors affect the curative effect of moxibustion, such as the meridians and acupoints selection, the time of moxibustion, the amount of moxibustion and so on. there is a lot of uncertain information, lacking of regularity of the excavation, which has...
In order to recover high-level software architecture from existing systems, we define Weighted Directed Class Graph(WDCG) to represent object-oriented software in this paper, which not only reflects static information of lowest level composition of software but also reflects dynamic information of software running. A new hybrid clustering algorithm based on hierarchical clustering and partition clustering...
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