Search Results - (( developing set means algorithm ) OR ( java implication based algorithm ))
Search alternatives:
- implication based »
- java implication »
- means algorithm »
- developing set »
-
1
Optimized clustering with modified K-means algorithm
Published 2021“…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
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 -
3
A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm requires two inputs for it to be applied onto a data set, the value K, and a proximity measure. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
4
Improved clustering using robust and classical principal component
Published 2017“…The classical k-means algorithm and the k-means by PCA algorithm are very sensitive to the presence of outlier. …”
Get full text
Get full text
Thesis -
5
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
Get full text
Get full text
Thesis -
6
Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
Get full text
Get full text
Conference or Workshop Item -
7
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
Get full text
Get full text
Thesis -
8
The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
Get full text
Get full text
Thesis -
9
-
10
Logistic regression methods for classification of imbalanced data sets
Published 2012“…This thesis aims to develop the simple and effective imbalanced classification algorithms by previously improving the algorithms performance of general classifiers i.e. …”
Get full text
Get full text
Thesis -
11
Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
Get full text
Get full text
Get full text
Thesis -
12
Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
Get full text
Get full text
Article -
13
Noise Cancellation method in assistive listening system
Published 2020“…Those algorithms were Least Means Square, Normalize-Least Means Square, Recursive Least Square, Simple SetMembership Algorithm and Dynamic Set-Membership Affine Projection Algorithm. …”
Get full text
Get full text
Undergraduates Project Papers -
14
Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The performances ofthese aggregation algorithms ofNNs ensemble were evaluated with the mean absolutepercentage error and symmetric mean absolute percentage error. …”
Get full text
Get full text
Thesis -
15
Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Several features have been extracted from heart rate, systolic and diastolic blood pressure. There are 8 set of feature selection model has built and a total of 24 set of classifiers with 3 different type of classification techniques were developed. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
16
A Mobile Application For Stock Price Prediction
Published 2021“…The evaluation methods were Root Mean Square Error and Mean Absolute Error. The results show ARIMA has the least error among all five prediction algorithms. …”
Get full text
Get full text
Final Year Project / Dissertation / Thesis -
17
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
Get full text
Get full text
Article -
18
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
Get full text
Get full text
Thesis -
19
Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…In prediction setting the proposed algorithms showed 4dp to 8dp higher prediction gain than other algorithms. …”
Get full text
Get full text
Get full text
Thesis -
20
Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing
Published 2017“…The experimental result shows that elitism enhanced the performance of MBO as the mean of the best generated test cases for MTS-e is better than the mean generated by benchmarked strategies.…”
Get full text
Get full text
Article
