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Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

“…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

“…The performance of the proposed algorithm is also compared to the model developed using the orthogonal least squares (OLS) algorithm. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary by Mohd Zamary, Nurul Aida

“…This project aims to develop a decision-making support model for diabetes diagnosis and treatment recommendation using the decision tree algorithm. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…Given the NP-Hard nature of the three models proposed in this thesis, two metaheuristic algorithms have been developed. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

“…First, NPR development is developed using three different algorithms which are Levenberg-Marquart (LM), Bayesian Regularization (BR) and Scaled Conjugated Gradient (SCG) to propose the best network algorithm using 70% training and 10-28 hidden neurons. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”

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 best model achieved in this study will be used as a platform of controller development using active vibration control technique.…”
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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

“…To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. …”
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Stereolithography 3D printing development of 3D printing machine controller using the predefined closest-distance volume interpolator system by -, -

“…The proposed slicing algorithm uses line-plane intersection model to generate arbitrary line segment when it receives an STL facet. …”
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Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

“…The plate is subjected to different disturbance signals and linear parametric models characterising the inputloutput dynamic behaviour of the plate, between two measurement points, is developed using RLS, RCGA, PSO and AIS algorithms. …”
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SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

“…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

“…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

“…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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Identification algorithms of flexible structure using neural networks by Ismail, R., Ismail, A. Y., Mat Darus, I. Z.

“…Furthermore, non-parametric models of the system are developed using Multi-layer Perceptron Neural Networks (MLP-NN) and Elman Neural Networks (ENN). …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…Furthermore, our CGD algorithms are also capable of estimating the pure GARCH model, unlike any similar algorithm for the same model in the literature. …”
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