Search Results - (( parameter optimization approach algorithm ) OR ( using function machine algorithm ))
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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Forecasting FTSE Bursa Malaysia KLCI Trend with Hybrid Particle Swarm Optimization and Support Vector Machine Technique
Published 2013“…The SVM algorithm uses the Radial Basis Function (RBF) kernel function and optim ization of the gam ma and large margin parameters are done using the PSO algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Parametric Optimization of End Milling Process Under Minimum Quantity Lubrication With Nanofluid as Cutting Medium Using Pareto Optimality Approach
Published 2016“…In this paper a genetic algorithm based multi-objective optimization approach is applied in order to predict the optimal machining parameters for the end milling process of aluminium alloy 6061 T6 combined with minimum quantity lubrication (MQL) conditions using waterbased TiO2 nanofluid as cutting fluid. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…The method has been optimized with the best parameters selected; c = 100, E = 10-6 and ex = 2 for non linear kernel function. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The gradient descent optimization algorithm was observed to help improve the modelâ��s performance. …”
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Intelligent approach for processmodelling and optimization on electrical dischargemachining of polycrystalline diamond
Published 2020“…Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Intelligent approach for process modelling and optimization on electrical discharge machining of polycrystalline diamond
Published 2018“…Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Novel farmland fertility algorithm based PIDPSS design for SMIB angular stability enhancement
Published 2020“…A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed for optimal design of PIDPSS using a robust ISTSE objective function which had to be minimized. …”
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Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales
Published 2018“…Genetic Algorithm is applied to the product design parameters to create a feedback system in order to get the best possible product design solutions with the least environmental impact within the product design functionality limitation. …”
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Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms
Published 2023“…The data obtained from the valorization of the biomass can be employed to model the process for the purpose of understanding the relationship between the input and targeted parameters thereby optimizing the process. This study employs a data-driven approach to model biochar production from agricultural wastes. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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