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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The Wilcoxon signed ranked statistical test shows that the ssSKF algorithm that uses an adaptive local neighbourhood in the prediction phase performs statistically better than the SKF algorithm that uses the last estimated state as its prediction, especially in solving high dimensional functions. …”
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2
Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The PSO1 algorithm which used first main temperature objective function gives the best roughness value (0.52 μm) compared with other algorithms, followed by the AIS2 and PSO2 that give (0.86 μm). …”
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Evapotranspiration prediction using system identification and genetic algorithm
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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model
Published 2023“…Three different kernel functions were used in PSO-SVR (Linear, Polynomial, and RBF kernel) shows that PSO-SVR algorithm with RBF function had better accuracy than other kernel functions. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Two of the most frequently applied algorithms to model species-habitat relationships are Generalised Linear Models (GLM) and Random Forest (RF). …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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PREDICTIVE MAXIMUM POWER POINT TRACKING (MPPT) ALGORITHM FOR PERMANENT EXCHANGE MEMBRANE FUEL CELL (PEMFC)
Published 2022“…The focus of this project is to show the power characteristics extracted from the PEMFC system by using predictive control. A comparison of PEMFC performances based on the proposed technique with other existing MPPT algorithms will be done to validate the algorithm performance. …”
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Final Year Project Report / IMRAD -
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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10
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner
Published 2022“…The iterative process of Broyden's approach is nearly identical to Newton's method. Meanwhile, the Levenberg-Marquadt method uses the gradient descent algorithm, which also has a similar algorithm to the Gauss-Newton method in finding the value for the unknown parameter.…”
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Student Project -
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Characterization of dumping soil and settlement prediction using Monte Carlo approach
Published 2013“…These models are soil mechanics based model, Bjarngard and Edgers model, Power Creep function, hyperbolic function and rheological function. …”
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SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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Final Year Project -
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Enhancing the Yolov8 algorithm for real-time dental segmentation
Published 2025“…The novelty of this work lies in improving the Coordinates-To-Features (C2f) module, for which its equations were derived, and in employing gradient-descent-based methods in the loss function to reduce loss and achieve the highest prediction accuracy. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There have two most uses activation function namely tansig and logsig. …”
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Modeling and Prediction of The Mechanical Properties of Feedstock by Cooling-Slope Casting Process using MOJaya Algorithm
Published 2024“…Hence, computational methods namely the MOJaya algorithm are utilized to model and optimize the parameters of CS to address the CS problem and forecast the performance of the feedstock. …”
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Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System
Published 2021“…This predictive MPPT includes the predictive control algorithm of a DC-DC boost converter in the fully functional mathematical modeling of the PEMFC system. …”
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Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure
Published 2016“…Several important criteria for a desirable model structure include its accuracy in future prediction and model parsimony. …”
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