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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters
Published 2025“…The PSO algorithm achieved two optimal mean surface roughness values of 0.9333 µm and 0.9838 µm, with an overall average of 0.9399 µm and a standard deviation of 0.0171 µm across 250 runs. …”
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Surface roughness optimization in end milling using the multi objective genetic algorithm approach
Published 2012“…This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. …”
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Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm
Published 2012“…Machining of hard materials at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality. Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the cutting temperatures and surface roughness becomes utmost important to avoid any damage to the quality surface.This paper presents the development of new models and optimizing these models of machining parameters to minimize the cutting temperature in end milling process by integrating the genetic algorithm (GA) with the statistical approach. …”
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Proceeding Paper -
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Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer
Published 2024“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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Multi objective optimisation for high speed end milling using simulated annealing algorithm
Published 2015“…This paper presents the optimization of machining parameters in end milling processes by using the simulated annealing algorithm (SAA) as one of the unconventional methods in optimization. …”
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Optimization of super twisting sliding mode control gains using Taguchi method
Published 2018“…The optimization method applied a L9 orthogonal array and the performance index used was root mean square of tracking error and Fast Fourier Transform of control inputs. …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…Multiple response optimization (MRO) problems need to optimize several response variables simultaneously. …”
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Evaluation of contemporary computational techniques to optimize adsorption process for simultaneous removal of COD and TOC in wastewater
Published 2022“…The adsorption parameters were optimized using ANFIS-surface plots, ANN-GA hybrid, RSM-GA hybrid, and RSM optimization tool in design expert (DE) software. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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A computational approach for optimizing vehicles' interior noise and vibration
Published 2017“…This paper proposes a Genetic Algorithm (GA) to optimise vehicles’ interior noise and vibration caused by powertrain, tire-road surface interaction and type of car. …”
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A computational approach for optimizing vehicles’ interior noise and vibration
Published 2017“…This paper proposes a Genetic Algorithm (GA) to optimise vehicles’ interior noise and vibration caused by powertrain, tire-road surface interaction and type of car. …”
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Sustainable synthesis processes for carbon dots through response surface methodology and artificial neural network
Published 2019“…The predictions for fluorescent CDs synthesis from RSM were in excellent agreement with the artificial neural network (ANN) model prediction by the Levenberg–Marquardt back propagation (LMBP) algorithm. Considering R2, root mean square error (RMSE) and mean absolute error (MAE) have all revealed a positive hidden layer size. …”
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Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater
Published 2022“…The adsorption parameters were optimized using ANFIS-surface plots, ANN-GA hybrid, RSM-GA hybrid, and RSM optimization tool in design expert (DE) software. …”
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Optimal Fuzzy logic controller based Genetic Algorithm for control maximum power point tracking for Boost Converter
Published 2025Conference paper -
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FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS
Published 2023“…The fingerprint consists of valleys and ridges on the surface of a fingertip. In this paper, a new hybrid strategy Particle Swarm Optimization (PSO) with Bat Algorithm (BA) is proposed to extract features from fingerprint images. …”
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Optimization of waterjet paint removal operation using artificial neural network
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Ultrasound-assisted process optimization and tribological characteristics of biodiesel from palm-sesame oil via response surface methodology and extreme learning machine - Cuckoo s...
Published 2020“…Extreme learning machine (ELM) and response surface methodology (RSM) techniques were used to model the production process and the input variables (time, catalyst amount, methanol to oil ratio, and duty cycle) were optimized using cuckoo search algorithm. …”
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