Search Results - (( variable training model algorithm ) OR ( java application testing algorithm ))
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1
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. …”
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2
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. …”
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Final Year Project -
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. …”
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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. …”
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5
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…In preprocessing of optimization, modeFrontier Response Surface Method (RSM) is able to model the behavior of engine performances corresponding to the change of design variables.…”
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Proceeding Paper -
6
Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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Monograph -
7
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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8
Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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9
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. …”
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10
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. …”
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Thesis -
11
Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Model built resulted in variables importance’s ranking and subsequently, prediction can be made. …”
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Final Year Project -
12
Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…Also, the model performance was characterized based on the number of input variables utilized. …”
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13
Developing a model to predict mathematics performance using neural network / Normaziah Abdul Rahman, Fadzilah Siraj and Noor Aishikin Adam
Published 2006“…This model allows the system administrator to train and normalize data as well as trains. …”
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Research Reports -
14
Academic Achievement Prediction Model Using Neural Networks
Published 2002“…This model allows the system administrator to train and normalize data as well as trains. …”
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Thesis -
15
Daily streamflow forecasting using simplified rule-based fuzzy logic system
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16
Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model
Published 2001“…In this paper, major properties of an adaptive fuzzy model as a system identifier when trained by the back-propagation algorithm are discussed. …”
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17
Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia
Published 2023“…This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). …”
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18
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. …”
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Thesis -
19
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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20
Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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