[PDF] Top 20 Liquefaction Prediction Using Rough Set Theory

... of liquefaction is one of the most important issues of geotechnical ...engineering. Liquefaction prediction depends on many factors, and the relationship between these factors is non-linear and ...on ... See full document

... research, Rough set is applied to improve feature selection and data ...the rough set feature reduction to effectively classify stock ...by using Rough set, the ... See full document

... Rough set theory is a mathematical tool which deals with ...of rough set is originated assuming the fact that some information is always associated with every object that exists in the ... See full document

... final prediction and associ- ated score are presented by the ...the prediction further supported by the set of rules from which said pre- diction ...obtained using C4.5 can be repre- sented as ... See full document

... mining. Prediction through classification is one of the common techniques used in data mining ...apply rough set theory KDD method to classify and analyse customer churn in Telecommunication ... See full document

... Intrusion detection plays a vital role in the security of communication. IDS must be intelligent enough to have high detection rate with the less false positive rate. The high amount of data and irrelevant, redundant ... See full document

... function prediction process is the important concept in the data mining process to classify the several problems ...data set that uses the sequence analyzing and classification ...data set is, it has ... See full document

... all rough set theory is also treated as a pivotal approach which deals with vagueness and uncertainty emphasized in decision ...1982 rough set theory [17-20] was introduced by ... See full document

... [1] Discusses about the situation of the country after the arrival of demonetization. The nature of the paper is very descriptive. [1] has covered the consequences, advantages and the disadvantages which were brought by ... See full document

... Fuzzy Rough Instance Selection method along with weak gamma evaluator as a measure for instance selection and fuzzy rough nearest neighbor classifier for classification ...test set is defined as the ... See full document

... Discretization is the process to transform continuous features into qualitative features. Firstly, continuous feature values are divided into subintervals. Then, each interval is mapped to a discrete symbol (categorical, ... See full document

... The rough sets theory introduced by Pawlak 13 has often proved to be an excellent mathematical tool for the analysis of a vague description of objects called actions in decision ...by rough sets ... See full document

... denotes a k-partition of X , and X denotes the complete set of all items that we want to cluster. For instance, X = { a , b , c , d , e , f }, k = 3 and P = {{ a , b , c }, { d }, { e , f }}The diameter of cluster ... See full document

... 1980’s Rough Set Theory Zdzislaw I. Pawlak developed the Rough Set Theory ...This theory deals with the classification analysis of data ...the Rough Set ... See full document

... T x y U x M y (8) By transposing, we get a set, for each object in this set, its minimal description containing x , that means the object x has relation with all objects in the set. and the ... See full document

... Abstract— Intrusion detection systems are used to identify and report intrusions in order to take necessary remedial actions. For any mining and classification problem, pre-processing and feature selection plays an ... See full document

... • Interestingly many semantics of general RST do not make use of any ’rough inclusions’ at all as their intent is not to describe ’roughly equivalent objects’. Example: Cattaneo’s BZ-algebras and variants. • In ... See full document

... of rough knowledge reduction focused on the existing complex, large-scale data sets of task mapping iterative reduction, get sub view equivalence class task after the update, time cost of task sets the optimal ... See full document

... by using the wireless network depends on the provided features by the device itself in terms of power limitations to communicate and the difference in screen size ... See full document

... characteristics using automatic ...By using clustering technique, we can keep books that have some kinds of similarities in one cluster or one shelf and label it with a meaningful ... See full document