Search Results - (( variable implementation clustering algorithm ) OR ( java application mining algorithm ))
Search alternatives:
- implementation clustering »
- variable implementation »
- application mining »
- java application »
- mining algorithm »
-
1
Direct approach for mining association rules from structured XML data
Published 2012Get full text
Get full text
Thesis -
2
-
3
A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…Next, we also optimize the fuzzification variable, m in FCM algorithm in order to improve the clustering performance. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
4
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
Get full text
Get full text
Get full text
Article -
5
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
Get full text
Get full text
Thesis -
6
Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
7
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
8
Mining Sequential Patterns using I-PrefixSpan
Published 2008Get full text
Get full text
Citation Index Journal -
9
-
10
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
Get full text
Get full text
Thesis -
11
Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control
Published 2014“…Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. …”
Get full text
Get full text
Get full text
Article -
12
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
Get full text
Get full text
Thesis -
13
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
Get full text
Get full text
Thesis -
14
An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…The existing research in traffic speed prediction used LSTM with single variable (traffic speed) and multi variables (traffic speed and vehicle headway). …”
Get full text
Get full text
Get full text
Thesis -
15
Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system
Published 2025“…The results reveal that while the K-means clustering method outperforms the Variable Bin Width method across several performance metrics, including an accuracy of 86.36% and a high specificity of 94.5%, the method’s recall rate of 50.49% indicates room for improvement in identifying true positives. …”
Get full text
Get full text
Get full text
Article
