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1
Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization
Published 2014“…The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. …”
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Article -
2
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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Thesis -
3
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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4
The application of queuing theory model using the DSW Algorithm and the L-R Method to optimize customer flow at Pizza Hut / Anis Natasha Mohamad Nizam, Nurfatihah Nadirah Noor Azla...
Published 2022“…This study aims to compare the behaviors of a queuing system at an order counter using the Fuzzy Queuing Model, which are the Dong, Shah, and Wong (DSW) Algorithm and the Left-Right (L-R) Method. …”
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Student Project -
5
Improved opposition-based particle swarm optimization algorithm for global optimization
Published 2021“…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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6
A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine
Published 2025“…The numerical experimental results demonstrated that the ABWO algorithm beat all other optimization methods and could solve the majority of the benchmark functions. …”
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7
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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8
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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9
Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
Published 2018“…In this study, the uncertainty and nonstationary characteristics of streamflow data has been treated using a set of coupled data pre-processing methods before being considered as input for an artificial neural network algorithm namely; rolling mechanism (RM) and grey models (GM). …”
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10
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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Thesis -
11
Improving neural networks training using experiment design approach
Published 2005“…This project involves the use of Neural Networks (NN) for function approximation. …”
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Thesis -
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Power System State Estimation In Large-Scale Networks
Published 2010“…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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14
A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Monograph -
15
A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
16
Modelling transmission dynamics of covid-19 during Pre-vaccination period in Malaysia: a predictive guiseird model using streamlit
Published 2023“…The mathematical model is solved using Scipy odeint function, which uses Livermore Solver for Ordinary Differential Equations with an Automatic method switching (LSODA) algorithm. …”
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Proceeding Paper -
17
Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network
Published 2021“…Second, a sine cosine algorithm is presented to optimize neural network for infilling the missing rainfall data. …”
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18
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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19
Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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20
Modified Seird model: a novel system dynamics approach in modelling the spread of Covid-19 in Malaysia during the pre-vaccination period
Published 2023“…The mathematical model is solved numerically using built-in Python function ‘odeint’ from the Scipy library, which by default uses LSODA algorithm from the Fortran library Odepack that adopts the integration method of non-stiff Adams and stiff Backward Differentiation (BDF) with automatic stiffness detection and switching. …”
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