Search Results - (( model validation drops algorithm ) OR ( criteria classifications using algorithm ))

Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

“…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later refined to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
Get full text
Get full text

Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

“…Algorithms are used to find the solutions through the computer program. …”
Get full text
Get full text

Mathematical modelling of mass transfer in multi-stage rotating disc contactor column by Arshad, Khairil Anuar, Talib, Jamalludin, Maan, Normah

“…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later re¯ned to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
Get full text
Get full text
Get full text

Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

“…The use of information gain in the ID3 algorithm as the attribute selection criteria is not to assess the relationship between classification and the dataset’s attributes. …”
Get full text
Get full text
Get full text

A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
Get full text
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
Get full text
Get full text
Get full text

Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
Get full text
Get full text
Get full text

Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

“…Three phase flow data have been collected from different geographical locations; especially from Middle-Eastern fields in order to construct, test, and validate the model. The data covered a wide range of variables such as oil rate (up to 25000 STB/D), water cut (up to 60%), angles of inclination (from -80 to 210), pipe length up to 26.0 km and pressure drop (from 10 to 250 psi). the model has been generated using the Back-propagation technique with Bayesian Regularization training algorithm for predicting pressure drop in pipelines under various angles of inclination. …”
Get full text
Get full text

Winsorize tree algorithm for handling outliers in classification problem by Ch’ng, Chee Keong

“…This study proposes a modified classification tree algorithm called Winsorize tree based on the distribution of classes in the training dataset. …”
Get full text
Get full text
Get full text

Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

“…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
Get full text
Get full text
Get full text

ANALYSIS AND OPTIMIZATION OF HYDROCYCLONE GEOMETRY USING BOX-BEHNKEN AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM by MOHD NOR, MOHD AZRI

“…Therefore, the objectives of this research are to investigate hydrocyclone geometrical parameters impact onto performance (pressure drop, flow split and separation efficiency) using Box-Behnken, analysis of multivariate analysis of variance of geometrical parameters against performances and investigate and validate the effectiveness of multi objective optimization algorithm. …”
Get full text
Get full text

DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

“…The ANN model has been developed using resilient back-propagation learning algorithm. …”
Get full text
Get full text

Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance by Haithm Haithm, ALSHARI, Abdulrazak Yahya, Saleh, Alper, ODABAŞ

“…Then we use a variety of performance criteria to evaluate their performance. …”
Get full text
Get full text
Get full text

Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs by Afshar Ghotli, Reza, Abbasi, Mohammad Reza, Bagheri, AmirHossein, Abdul Raman, Abdul Aziz, Ibrahim, Shaliza, Bostanci, Huseyin

“…Adaptive neuro-fuzzy inference system based on fuzzy C–means (ANFIS-FCM) clustering algorithm was used to develop a model to predict drop sizes, and its validation and accuracy were examined by comparing the results to the experimental data. …”
Get full text
Get full text

Driver drowsiness detection using different classification algorithms by Nor Shahrudin, Nur Shahirah, Sidek, Khairul Azami

“…Hence, this paper present and prove the reliability of ECG signal for drowsiness detection in classifying high accuracy ECG data using different classification algorithms.…”
Get full text
Get full text
Get full text
Get full text

Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

“…From a group of 1480 patients drawn from the Acute Coronary Syndrome Malaysian registry, 302 people satisfied the inclusion criteria, and 54 variables were duly considered. Combinations of feature selection and classification algorithms were used for mortality prediction post ACS. …”
Get full text
Get full text
Get full text

Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

“…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
Get full text
Get full text

Classification of Rheumatoid Arthritis using Machine Learning Algorithms by Sharon, H., Elamvazuthi, I., Lu, C.K., Parasuraman, S., Natarajan, E.

“…Furthermore, this database which consists of 8 attributes and 32 instances, are used to determine the performance in terms of accuracy for the classification of different algorithms. …”
Get full text
Get full text

Power quality problem classification based on Wavelet Transform and a Rule-Based method by Nallagownden, Perumal

“…The model is tested by using MATLAB toolbox. The simulation produces satisfactory result in identifying the disturbance and proof that it is possible to use this model for power disturbance classification. …”
Get full text
Get full text