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Aiming at the knowledge mining from fuzzy and uncertain information, the definition mode and properties of the fuzzy formal context are discussed in the paper. The method of constructing the fuzzy concept lattice of the fuzzy formal context is proposed, in that the definition of fuzzy product concept is the core: the intents of two concepts are combined to form the intent of the product concept; using...
This The index system of environmental impact assessment of tailings pond is hierarchal structure. As there is inherent uncertainty in determining the evaluation grade of low-level indicators and the relationship between the up-level and low-level indicators is non-linear, therefore, the evaluation model should have to deal with the uncertainty of information and achieve the non-linear conversion...
As a branch of Group Decision-Making Method, Grade division plays an important role in many applications such as hazard assessment, quality evaluation, and performance inspection and so on. At present, the most popular grade division method is fuzzy comprehensive evaluation, which determines the decision objects' grade through analysis of evaluation vector. One problem with this approach is that it...
First, we classify the objects in continuous domain decision table according to fuzzy clustering; then, combining rough set theory with fuzzy set theory, an attribute reduct algorithm of decision table with continuous attributes is put forward; at last, a rule extraction algorithm is proposed and also the validity of this algorithm is accounted for through an example.
As present, the relational database, which stores and processes a large number of crisp data, is in the dominant position, but in which some fuzzy requirements described in natural language are not supported well. The fuzzy database, which stores fuzzy data with a complex transition from crisp data, has not yet grown up. Try to do fuzzy queries, fuzzy semantic summary and test user's fuzzy rules here,...
Presently, in the data mining scenario clustering of large dataset is one of the very important techniques widely applied to many applications including social network analysis. Applying more specific pre-processing method to prepare the data for clustering algorithms is considered to be a significant step for generating meaningful segments. In this paper we propose an innovative clustering technique...
It is a technical difficulty that evaluation of student automatic learning under network environment. In this article, an on-line evaluation system and index system are set up base on fuzzy theory and level analysis method, furthermore, the system be testified working well through questionnaires of teachers, experts and students and practice in the process of network class.
Forecasting stock price time series is very important and challenging in the real world because they are affected by many highly interrelated economic, social, political and even psychological factors, and these factors interact with each other in a very complicated manner. This article presents an approach based on Genetic Fuzzy Systems (GFS) for constructing a stock price forecasting expert system...
The injection mould repair projects are viewed as very important knowledge in many mould manufacturers. With the increase of injection mould repair projects, knowledge induction of mould repair becomes the key to using knowledge effectively in making injection mould repair projects. Using the fuzzy rules induction to induce the injection mould repair rules and help the technician establishing the...
An algorithm for intrusion detection based on improved evolutionary semi- supervised fuzzy clustering is proposed which is suited for situation that gaining labeled data is more difficulty than unlabeled data in intrusion detection systems. The algorithm requires a small number of labeled data only and a large number of unlabeled data and class labels information provided by labeled data is used to...
Classification is one of the most popular data mining techniques applied to many scientific and industrial problems. Recently, fuzzy association rule has been extensively studied in classification. In this paper, a new classification model is proposed, which is based on interpretable fuzzy association rules and automatic generating membership functions. In addition,a modified algorithm for classification...
A new clustering classification approach based on fuzzy closeness relationship (FCR) is studied in this paper. As we know, fuzzy clustering classification is one of important and valid methods to knowledge discovery. One of problems in fuzzy clustering classification is to determine a certain fuzzy sample classification in given limited sample space. Another is its validity, that is to say, if the...
An approach based on data mining technology is put forward to evaluate the effect of tumor treatment. Firstly, cases are clustered according to the initial state of cancer patients, such as age, sex and tumor attributes. Second, the efficacy of magnetic therapy is classified based on pre and post information (mainly tumor image information) of the patient. After analyzing the images of cancer in magnetic...
Granular computing is the key to granular neural networks, and in fact it is also the main problem in knowledge discovery and data mining. This paper addresses fuzzy information extraction and granular computing in granular neural networks in order that fuzzy rules can be discovered from fuzzy information which is difficult to be measured accurately with numerical data and furthermore the missing...
The primary purpose of the data mining is extraction of required information from a huge amount of datasets. In this regard, it must be tried to omit invalid, noisy and incomplete information as far as possible. Our results and assessment from data mining process would be incomplete, while this information is not omitted totally. It means, if the creditable value according required content has not...
To improve the intelligibility and efficiency of knowledge expression for the land evaluation, a land evaluation method combining simplified fuzzy classification association rules with fuzzy decision is proposed in this paper. To reduce the complexity of the land evaluation models and improve the efficiency and intelligibility of fuzzy classification association rules further, an algorithm to eliminate...
It is very hard to acquire the information what you really want with the accumulation of large amount of data. Data mining technology has been achieved a great progress with the rapid development of computer science, artificial intelligence, and warehouse. City planning is a job with strong subjective which promotes the development of digital city planning. This makes an increasing demand of data...
Skyline cube is the crucial mechanism in multidimensional skyline queries and preference analysis, and has attracted much attention recently in knowledge management community. This is mainly due to the importance of skyline cube in many applications, such as data mining and visualization, user-preference queries, and multi-criteria decision making. In this paper, we propose a novel multidimensional...
Discovery the association between web pages is an important task as the rapid growth of web data. This article uses the fuzzy method to discover generalized fuzzy association rules among theWeb pages fromWeb logs. In the paper, whether a web page is visited or not and time duration on it are considered two important factors to reflect users' interest and preference. Numerical time duration is fuzzified...
Data mining methods have been proven effective in extracting knowledge from existing data sources for the classification of soils. Previous studies have suggested that soils are spatial entities with fuzzy boundaries and prompted the development of data mining methods to extract knowledge that allows for fuzzy classifications of soils. This paper first looks at the nature of soil classification from...
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