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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper aims to demonstrate the effectiveness of Multi- Objective Genetic Algorithm Optimization and its robust practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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2
Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Two main aspects are used to classify the evolutionary algorithm variants: population-based and evolutionary strategies (variation and replacement). …”
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3
Application of Multi-objective Genetic Algorithm (MOGA) for design optimization of valve timing at various engine speeds
Published 2011“…This paper aims to demonstrate the effectiveness of Multi-Objective Genetic Algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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4
Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. …”
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5
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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Thesis -
6
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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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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8
Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances
Published 2023“…Algorithms are simulated with the help of MATLAB�and Simulink�. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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10
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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11
Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors
Published 2023“…Climate models; Climatology; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Mean square error; Particle swarm optimization (PSO); Principal component analysis; Stream flow; Adaptive neuro-fuzzy inference system; ANFIS-PSO; Climate index; Confidence levels; ENSO; Probability spaces; Root mean square errors; Streamflow simulations; Fuzzy inference; assessment method; El Nino-Southern Oscillation; genetic algorithm; index method; model; prediction; seasonal variation; streamflow; uncertainty analysis…”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…The training data required to train the two-metamodeling techniques were generated using a verified nonlinear finite element algorithm developed in the current research. …”
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13
Analysis of inverted planar perovskite solar cells with graphene oxide as HTL using L9 OA Taguchi method
Published 2024“…By using this method, the data from the numerical modelling Solar Cell Capacitance Simulator-One Dimensional (SCAPS-1D) was optimized. …”
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Analysis of Inverted Planar Perovskite Solar Cells with Graphene Oxide as HTL using L9 OA Taguchi Method
Published 2025“…By using this method, the data from the numerical modelling Solar Cell Capacitance Simulator-One Dimensional (SCAPS-1D) was optimized. …”
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15
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…Finally the adaptive portion of FLC is applied in order to compensate the effect of unknown parameter variations in the Pico-satellite system by using an adaptable gain which is connected in the forward path of the FLC. …”
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Predictive Maximum Power Point Tracking for Proton Exchange Membrane Fuel Cell System
Published 2025“…However, fluctuations in the internal parameters of PEMFC can cause variations in power output. …”
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18
A multi-period scheduling of dynamic cellular manufacturing systems in the presence of cost uncertainty
Published 2016“…In continue a Taguchi method (an orthogonal optimization) is used to estimate parameters of the proposed method in order to solve experiments derived from literature. …”
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Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms
Published 2025“…Simulation results show that A-ORB outperforms conventional techniques such as small step perturb and observe (SS-PO), small step incremental conductance (SS-InC), and bio-inspired particle swarm optimization (BI-PSO) in both tracking accuracy and power output. …”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach
Published 2024“…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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