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1
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…The behavior of Genetic Algorithm (GA) where it generates and evolves the parameters towards a high-quality solution gives an advantage in obtaining ideal combination of parameters to fit in with the simulation. …”
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Final Year Project -
2
Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System
Published 2014“…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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3
Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System
Published 2014“…This paper explores the applications of two swarm intelligence algorithms in optimizing the PID controller parameters. …”
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4
Kinetic Parameter Estimation in Alkylation of Benzene with 1-Decene through Hybrid Particle Swarm Optimization
Published 2012“…Afterwards, the solution obtained using PSO algorithm is given as initial guesses to the Levenberg–Marquardt algorithm to determine the improved optimal solution. …”
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Final Year Project -
5
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Thesis -
6
Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling
Published 2011“…Based on the simulated annealing (SA) algorithm, a scheduling method is proposed to solve the problem in a relatively short period of time. …”
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7
Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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8
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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9
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper involves engine modeling in 1D software simulation environment, GT-Power. …”
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Proceeding Paper -
10
Simulated real-time controller for tuning algorithm using modified hill climbing approach
Published 2014“…That led to new ways to tackle old problems like model inaccuracies and inconsistencies. Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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11
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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12
Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi
Published 2015“…The initial feasible solutions have been generated for this purpose. The solutions have been significantly improved by the algorithms. …”
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13
Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The evaluation process employs the Hypervolume (HV) indicator and Inverted Generational Distance (IGD) to scrutinize solution efficacy and coverage. The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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14
Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks
Published 2018“…The selected algorithms for the reduction algorithm in the transmissions include Move Average algorithm (MA), Autoregressive all-pole model parameters — Burg’s algorithm. …”
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15
Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Therefore, in this project, Principal Component Analysis (PCA) is used to reduce the number of parameters. The project is divided to several steps; in which the first step is to develop a conceptual model which can be used to generate both synthetic historical data and also simulated data. …”
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Final Year Project -
16
Uncertain viscoelastic models with fractional order: a new spectral tau method to study the numerical simulations of the solution
Published 2017“…We propose here a new model based on fractional calculus to deal with the Kelvin–Voigt (KV) equation and non-Newtonian fluid behavior model with fuzzy parameters. …”
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Relative motion guidance, navigation and control for autonomous spacecraft rendezvous
Published 2011“…These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. …”
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Proceeding Paper -
18
An enhanced cluster head selection algorithm for routing in mobile AD-HOC network
Published 2017“…Inter-cluster routing corresponds to routing between two clusters using a Global Positioning System (GPS). A model for the Ad hoc network was simulated with various cluster scenarios. …”
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Thesis -
19
RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING
Published 2023“…Therefore, developing predictive proxy models using machine learning algorithms is a suitable solution to address this concern. …”
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20
Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algor...
Published 2007“…A hybrid artificial neural network-genetic algorithm (ANN-GA) was developed to model, simulate and optimize the catalytic-dielectric barrier discharge plasma reactor. …”
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