fuzzy association rules
FORCASTING OF FINANCIAL MARKETS - APPLICATION OF FUZZY ASSOCIATION RULES
... The fuzzy rule used in the model uses variance as rule based parameter for designing different ...variable. Fuzzy rules have been designed by considering the standard deviation of the above ...
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Evolving temporal fuzzy association rules from quantitative data with a multi objective evolutionary algorithm
... quantitative association rule mining is the crisp boundaries of discretised values that potentially hide rules and lose information ...attributes. Fuzzy association rules deal with ...
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Applying Fuzzy Fp-treeto Mine Fuzzy Association Rules Using Hedge Algebras Based Approach
... fuzzy association rules is mainly based on the theory of fuzzy set as shown in [6] ...using fuzzy, there are many factors affecting the accuracy such as determination of fuzzy ...
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Performance of Novel Based Fuzzy Association Rules to Reduced Computational Data Sets by Row Counts
... Based Fuzzy association rules for learning achievement mining, 2009 international conference on machine learning and computing IPCSIT vol3 (2011) IACSIT PRESS SINGAPUR for comparison with proposed ...
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Intrusion Detection System using Genetic-Fuzzy Classification
... of rules may not produce good performance and it makes difficult to understand the model ...of fuzzy association rules with high classification accuracy from the rule base, a GA model is used, ...
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Correlation Detection and Judgment of Abnormal Individual Behavior Based on Unsupervised Learning
... find fuzzy association rules between daily exercise and physiological health data based on unsupervised ...the fuzzy clustering method is used to transform the numerical attributes to ...
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Evolving temporal fuzzy itemsets from quantitative data with a multi objective evolutionary algorithm
... Fuzzy association rules [14] deal with the inaccuracies in physical measurements and better handle unnatural boundaries found in crisp ...Evolving fuzzy association rules [15] ...
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Mining Multilevel Fuzzy Association Rule from Transaction Data
... defined fuzzy set concepts, multiple level taxonomy and different minimum supports for each level and find fuzzy association rules in a given transaction data ...by fuzzy set concepts. ...
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Online Full Text
... In many cases, the number of intervals associated with an attribute is large hence when we join the attributes in the mining process, the number of itemsets (i.e., a set of <attribute, interval> pairs) can become ...
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Improvement of Mining Fuzzy Multiple Level Association Rules from Quantitative Data
... mining association rules identify relationships among transactions using binary values and find rules at a single-concept ...multilevel association rules in transaction databases is ...
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Discovery of Fuzzy Hierarchical Association Rules
... relating fuzzy sets and association rules. In their work, fuzzy sets are introduced to diminish the granularity of quantitative attributes ...change fuzzy transactions into crisp ones ...
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Online Full Text
... Specified fuzzy linguistic terms in fuzzy association rules can be given only when the properties of the attributes are ...i.e., fuzzy association rules with enough ...
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Temporal fuzzy association rule mining with 2 tuple linguistic representation
... mines fuzzy association ...all fuzzy association rules that are above user specified thresholds, minimum support and minimum ...discovers fuzzy association rules ...
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Online Full Text
... 3. OUR ALGORITHM (FCBAR) The performance is dramatically decreased in the process of many fuzzy association rule algorithms. This is due to the fact that a database is repeatedly scanned to contract each ...
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International Journal of Computer Science and Mobile Computing
... the fuzzy c-means (FCM) method which is used to obtain the mean and standard deviation (std) of I/P/B frame sizes when the frame category is ...type-2 fuzzy logic classifiers (FLCs) to classify video ...
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The Smith-PID Control of Three-Tank-System Based on Fuzzy Theory
... 2009); Fuzzy Immune Adaptive Smith-PID Control for Water Quality Adjusting System of Thermal Power Plant (Wuhan, China, The 2nd International Workshop on Intelligent Systems and Applications (ISA2010), 2010); The ...
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Online Full Text
... A crossover operation is applied to a selected random pair of fuzzy if–then rules with a pre-specified crossover probability. Note that the selected individuals for crossover operation should be different. ...
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An Improved Fuzzy-based Image Filtering for High Density Salt and Pepper Noise
... a fuzzy switching filter to remove high density salt and pepper noise in an ...proposed fuzzy median filter and the proposed fuzzy mean ...proposed fuzzy median filter is ...proposed ...
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A Novel Fuzzy Based DC–DC Boost Converter with Balanced Output & High Voltage Gain
... time fuzzy- boost converter is used. In Fuzzy boost converter output voltage can be to step up and step down output voltage according to the variable duty ...the Fuzzy-boost converter and reference ...
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Fast Learning Algorithm for Fuzzy Inference Systems using Vector Quantization
... simulation, 5-fold cross-validation is used. Tables VII and VIII show the initial conditions for simulations and Table IX shows the result of classification for each algorithm. In Table IX, the number of rules, ...
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