Search Results - (( variable training test algorithm ) OR ( java application testing algorithm ))
Search alternatives:
- application testing »
- variable training »
- testing algorithm »
- java application »
- test algorithm »
- training test »
-
1
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
Get full text
Get full text
Final Year Project -
2
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
Get full text
Get full text
Article -
3
Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
Get full text
Get full text
Article -
4
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
Get full text
Get full text
Journal -
5
Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…Meanwhile, the AdaBoost algorithm achieved 99.1% sensitivity in the testing dataset. …”
Article -
6
Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…HEA is run on the training set in order to provide insights on the relationships between input variables and the algae abundance. …”
Get full text
Get full text
Thesis -
7
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…Mean absolute error (MAE), R-squared (R2), median absolute error (MeAE), mean absolute percentage error (MAPE) and mean Poisson deviance (MPD) are assessed after their training and testing of each algorithm. From the modeling of energy output data, it is seen that SVR (RBF) is the most suitable in providing very close predictions compared to other algorithms. …”
Get full text
Get full text
Get full text
Get full text
Article -
8
SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
Get full text
Get full text
Thesis -
9
Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…Meanwhile, the AdaBoost algorithm achieved 99.1% sensitivity in the testing dataset. …”
Get full text
Get full text
Get full text
Article -
10
Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
Get full text
Get full text
Final Year Project -
11
-
12
Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanopeprintss using artificial neural network (ANN)
Published 2016“…The performed experiments were designed into two data sets including training, and testing sets. To acquire the optimum topologies, ANN was trained by quick propagation (QP), Batch Back Propagation (BBP), Incremental Back Propagation (IBP), genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithms for testing data set. …”
Get full text
Get full text
Get full text
Article -
13
Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
Get full text
Get full text
Undergraduates Project Papers -
14
Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…The model had an impressive performance during the training phase, with a R2 of 0.98, RMSE of 2.412 MPa, and MAE of 1.6249 MPa when using 8 input variables to predict the compressive strength of concrete. …”
Article -
15
Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanoparticles using artificial neural network (ANN)
Published 2016“…The performed experiments were designed into two data sets including training, and testing sets. To acquire the optimum topologies, ANN was trained by quick propagation (QP), Batch Back Propagation (BBP), Incremental Back Propagation (IBP), genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithms for testing data set. …”
Get full text
Get full text
Get full text
Article -
16
Academic Achievement Prediction Model Using Neural Networks
Published 2002“…A training prediction of 90 % accuracy and testing prediction of 83.33% accuracy were achieved using this model. …”
Get full text
Get full text
Get full text
Thesis -
17
Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
Get full text
Get full text
Thesis -
18
Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…As for the implementation of MPCA in feature extraction for BOD and COD, there were only 4 inputs required to explain at least 99.999% variability for both analyses. Altogether, for BOD, the BR algorithm with 60% training and 12 hidden nodes gives R=0.7825 whereas for COD, the BR algorithm with 70% training and 10 hidden nodes gives R=0.6716. …”
Get full text
Get full text
Monograph -
19
-
20
Enhancing the entrepreneurial intention of the retiring military personnel through entrepreneurial training
Published 2017“…Partial Least Squares-Structural Equation Model (PLS-SEM) algorithm and bootstrap techniques were used to test the study hypotheses. …”
Get full text
Get full text
Get full text
Thesis
