Search Results - (( developing function machine algorithm ) OR ( based optimization method algorithm ))
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Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…It shows that optimization based on GA is capable of reducing production time in the machining process.…”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Test case generation from state machine with OCL constraints using search-based techniques / Aneesa Ali Ali Saeed
Published 2017“…The whole constraint analyzer and the fitness function were combined with four SBTs (genetic algorithm, evolutionary algorithm, simulating annealing, and quantum genetic algorithm). …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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Development of committee machine models for multiple response optimization problems
Published 2014“…There are several methods in two categories to solve MRO problems. The first category includes premier methods such as Response Surface Methodology (RSM) and Taguchi method and the second one includes newer methods like hybrid methods of ANNs and Genetic Algorithm (GA). …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm
Published 2020“…The PSSs design problem is transformed into an optimization problem which an eigenvalue-based objective function is developed and both the GA, PSO and the proposed FFA optimization methods are applied to search for the optimal control parameters of the PSSs that are connected to the multimachine in the power system. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Many machine learning algorithms excel at handling problems with conflicting objectives. …”
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Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems
Published 2012“…To solve the model, an algorithm based on Simulated Annealing (SA) is developed in C/C++ namely SA1. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…As such, its training can reach stability in a shorter time compared to the gradient-descent based methods. To achieve optimal RBFN-DDA performance, HS (or GSA) is proposed to optimize the center and the width of each hidden unit in a trained RBFN. …”
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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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Logistic regression methods for classification of imbalanced data sets
Published 2012“…However, the imbalanced LR-based methods are not extensively developed such as imbalanced SVM-based methods. …”
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HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets
Published 2018“…Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. …”
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Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
Published 2012“…This report presents optimization of abrasives machining of ductile cast iron using water based SiO2 nanocoolant. …”
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Undergraduates Project Papers -
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Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales
Published 2018“…A novel feature-based product design methodology based on an integrated CAD-LCA approach is developed which analyzes a product design’s environmental impact. …”
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