Search Results - (( java adaptation optimization algorithm ) OR ( construct ensemble learning algorithm ))

Pattern generation through feature values modification and decision tree ensemble construction by Akhand, M. A. H, Rahman, M.M. Hafizur, Murase, K.

Get full text
Get full text
Get full text

A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

“…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
Get full text
Get full text

An Improved Ensemble Deep Learning Model Based on CNN for Malicious Website Detection by Do N.Q., Selamat A., Lim K.C., Krejcar O.

An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

Get full text
Get full text
Get full text

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. Subsequently, the research attempts to construct an ensemble model applying Modified Grey Wolf Optimizer (MGWO) and neural network for stock prediction. …”
Get full text
Get full text

An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

“…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. Ensemble is a learning algorithm that combines some experts instead of considering a single best expert for the predictions.The thesis proposed anoptimizing method leading to small structure of assemble GA. …”
Get full text
Get full text

A Novel Hybrid Model for Forecasting China Carbon Price Using CEEMDAN and Extreme Learning Machine Optimized by Whale Algorithm by Li, Ni, Venus Liew, Khim Sen

“…This paper follows the idea of "primary decomposition- noise reduction-secondary decomposition- forecasting and integration", the contribution is constructing a hybrid carbon price forecasting model using Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Extreme Learning Machine (ELM) optimized by the Whale Optimization Algorithm (WOA). …”
Get full text
Get full text
Get full text

Pruned committee neural network based on accuracy and diversity trade-off for permeability prediction by Kenari, Seyed Ali Jafari, Mashohor, Syamsiah

“…In this paper, first we constructed a committee neural network with different learning algorithms and then proposed an expert pruning method based on diversity and accuracy tradeoff to improve the committee machine framework. …”
Get full text
Get full text
Get full text

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”

Modeling of mechanical properties of silica fume-based green concrete using machine learning techniques by Nafees, A., Amin, M.N., Khan, K., Nazir, K., Ali, M., Javed, M.F., Aslam, F., Musarat, M.A., Vatin, N.I.

“…A cross-validation technique was used to avoid overfitting issues and confirm the generalized modeling output. ML algorithms are used to predict SFC compressive strength to promote the use of green concrete. …”
Get full text
Get full text

Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete by Dai, L., Wu, X., Zhou, M., Ahmad, W., Ali, M., Sabri, M.M.S., Salmi, A., Ewais, D.Y.Z.

“…To fulfil this purpose, a standalone ML model called Multiple-Layer Perceptron Neural Network (MLPNN) and ensembled ML algorithms named Bagging and Adaptive Boosting (AdaBoost) were employed in this study. …”
Get full text
Get full text

Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
Get full text
Get full text
Get full text
Get full text