Search Results - (( data optimization model algorithm ) OR ( data collection means algorithm ))

Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

“…Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
Get full text
Get full text

A Single Objective Flower Pollination Algorithm for Modeling the Horizontal Flexible Plate System by Siti Zakiah, Maseri, Muhamad Sukri, Hadi, Annisa, Jamali, Hanim, Mohd Yatim, Mat Hussin, Ab Talib, Intan Zaurah, Mat Darus

“…The collected of real vibration data through experimental study was then utilized to develop the dynamic system model based on linear autoregressive with exogenous (ARX) model structure and optimized by flower pollination algorithm (FPA). …”
Get full text
Get full text
Get full text

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

“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
Get full text
Get full text

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
Get full text
Get full text

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
Get full text
Get full text
Get full text
Get full text

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…Upon the completion of data collection and data pre processing, the eABC-LSSVM algorithm is designed and developed. …”
Get full text
Get full text
Get full text

Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

“…In order to increase the performance of NNBP, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being hybrid with the ANN model to become Hybrid Neural Network Genetic Algorithm (HNNGA) model and Hybrid Neural Network Particle Swarm Optimization (HNNPSO) model respectively. …”
Get full text
Get full text
Get full text
Get full text

Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.] by M. A., Hambali, Y. K, Saheed, M. D, Gbolagade, M, Gaddafi

“…Researchers then performed data preprocessing on the data. Afterwards, data mining algorithms were applied in order to forecast electric load. …”
Get full text
Get full text
Get full text

Strut-and-tie model for externally bonded CFRP-strengthened reinforced concrete deep beams based on particle swarm optimization algorithm: CFRP debonding and rupture by Hanoon, Ammar N., Jaafar, M. S., Hejazi, Farzad, Aziz, Farah N .A. Abdul

“…The proposed model was validated using experimental data collected from the current study and existing literature. …”
Get full text
Get full text
Get full text

Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…For experimental purposes, a total of 6 independent inputs are considered which were collected based on daily weather data. The efficiency of the MFO-LSSVM, CSLSSVM, ABC-LSSVM, FA-LSSVM, and DE-LSSVM was quantitatively analyzed based on Theil’s U and Root Mean Square Percentage Error. …”
Get full text
Get full text

Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

“…The accuracy of the CNN model is comparable with the accuracy of the previous work that utilizing CNN for the imaging data to detect caries (diagnostic tool).…”
Get full text
Get full text

Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…For experimental purposes, a total of 6 independent inputs are considered which were collected based on daily weather data. The efficiency of the MFO-LSSVM, CS-LSSVM, ABC-LSSVM, FA-LSSVM, and DE-LSSVM was quantitatively analyzed based on Theil’s U and Root Mean Square Percentage Error. …”
Get full text
Get full text
Get full text

A Data Mining Approach to Enhancing Birth and Death Registration Processes by Erfan, Hasmin

“…The apriori algorithm refines registration data by identifying associations that reduce inconsistencies, while decision three analysis highlights critical factors contributing to registrations delays. a total 45 decision trees were generated, leading to policy recommendation aimed at improving data collection and public compliance. …”
Get full text
Get full text
Get full text
Get full text

Short-term PV power forecasting using hybrid GASVM technique by VanDeventer, William, Jamei, Elmira, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Tey, Kok Soon, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex

“…The GASVM model classifies the historical weather data using an SVM classifier initially and later it is optimized by the genetic algorithm using an ensemble technique. …”
Get full text
Get full text

Predicting real estate prices with AI: a comparative study of machine learning models by Lim, Eng-Lian, Wong, Doris Hooi-Ten, Masrom, Maslin

“…Model performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R2 on an 80:20 training-testing split. …”
Get full text
Get full text
Get full text
Get full text

3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
Get full text
Get full text

3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods by Hajihassani, M., Kalatehjari, R., Marto, A., Mohamad, H., Khosrotash, M.

“…To overcome these problems, the use of optimization algorithms to train ANNs is of advantage. …”
Get full text
Get full text

PID controller based on bird mating optimizer for vibration cancellation of horizontal flexible plate by Muhammad Farith Nazreen, Abu Samah, Muhamad Sukri, Hadi, Abdul Malek, Abdul Wahab, Nadzirah, Mohd Mokhtar, Intan Zaurah, Mat Darus

“…Initially, input–output experiment data is collected from previous researchers and utilized to model system development. …”
Get full text
Get full text
Get full text
Get full text

A dynamic eLearning prediction modelbased on incomplete activities of eLearning system by Chayanukro, Songsakda

“…Six data mining algorithms were used in evaluating the model. …”
Get full text
Get full text
Get full text
Get full text

The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
Get full text
Get full text