Search Results - using simulation mining algorithm
Search alternatives:
- simulation mining »
- mining algorithm »
-
1
Modeling and simulation of the industrial numerical distance relay aimed at knowledge discovery in resident event reporting
Published 2014“…This is justified by the practicality and necessity of divulging the decision algorithm hidden in the recorded relay event report using computational intelligence-based data mining. …”
Get full text
Get full text
Article -
2
A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
Get full text
Get full text
Get full text
Thesis -
3
-
4
Comparative analysis of danger theory variants in measuring risk level for text spam messages
Published 2024journal::journal article -
5
Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure
Published 2011“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
Get full text
Get full text
Thesis -
6
Finding objects with segmentation strategy based multi robot exploration in unknown environment
Published 2013“…Also the algorithm using segmentation strategy is using frontier base algorithm for exploring divided area. …”
Get full text
Get full text
Get full text
Article -
7
Data Mining On Machine Breakdowns And Effectiveness Of Scheduled Maintenance
Published 2019“…Data mining is the sixth step in which software of Orange is used as the tool. …”
Get full text
Get full text
Monograph -
8
-
9
-
10
Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…The simulation suggested that the proposed model outperformed the existing model in doing logic mining for the online shoppers dataset.…”
Get full text
Get full text
Get full text
Get full text
Article -
11
-
12
Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
Get full text
Get full text
Get full text
Article -
13
-
14
RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm
Published 2018Get full text
Get full text
Get full text
Conference or Workshop Item -
15
Distribution and health risk assessment of trace metals in freshwater tilapia from three different aquaculture sites in Jelebu Region (Malaysia)
Published 2015“…Results were compared with established legal limits and the daily ingestion exposures simulated using the Monte Carlo algorithm for potential health risks. …”
Get full text
Article -
16
Development Of Analytical Solution For Thermo-Mechanical Stresses Of Multilayered Pressure Vessel Based On Recursive Algorithm
Published 2022Get full text
Get full text
Final Year Project / Dissertation / Thesis -
17
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
Get full text
Get full text
Thesis -
18
-
19
A new text-based w-distance metric to find the perfect match between words
Published 2020“…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
Get full text
Get full text
Article -
20
Discretization of integrated moment invariants for writer identification
Published 2008“…Collectively, discrete values are finite intervals in a continuous spectrum of values and well known to play important roles in data mining and knowledge discovery. Many induction algorithms found in the literature requires that training data contains only discrete features and some works better on discretized data; in particular rule based approaches like rough sets. …”
Get full text
Get full text
Conference or Workshop Item
