Search Results - (( variable computationally efficient algorithm ) OR ( parameter optimization based algorithm ))
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1
Automatic control of flotation process using computer vision
Published 2015“…A control strategy based on froth model was then designed in order to optimize the visual characteristics of froth, which lead to the control of the metallurgical parameters in an indirect manner. …”
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2
The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…A simple three-term conjugate gradient algorithm for unconstrained optimization. Journal of Computational and Applied Mathematics, 241, 19-29.). …”
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3
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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4
Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment
Published 2018“…However, the previous algorithms are complicated and needed a lot of computational resources. …”
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5
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…The transformation results in an equivalent mixed discrete optimization problem. The transformed problemis then decomposed into a bi-level optimization problem, which is solved using a combination of an efficient discrete filled function method identified earlier and a computational optimal control technique based on the concept of control parameterization. …”
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6
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Optimization of medical image steganography using n-decomposition genetic algorithm
Published 2023“…The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. …”
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9
Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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10
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…The proposed strategy is dependent on modified Zimmermanns approach for handling all inexact operating costs, data capacities, and demand variables. The SD algorithm is employed to balance exploitation and exploration in MSA, thereby resulting in efficient and effective (speed and quality) solution for the APP model. …”
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11
Metaheuristic optimization of perovskite solar cell performance using Taguchi grey relational analysis with grey wolf optimizer
Published 2025“…Perovskite solar cells offer numerous benefits like simplified production, adaptability, and affordability in contrast to silicon-based counterparts. Yet, enhancing their power conversion efficiency remains difficult due to the diverse effects of various layer parameters variability. …”
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Article -
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Rank regression for modeling bus dwell time in the presence of censored observations
Published 2019“…Hence, this paper proposes rank estimators for modeling bus dwell time on the basis of Gehan and log-rank weight functions. An iterative algorithm is introduced that involves a monotone estimating function of the model parameter, and its minimization is a computationally simple optimization problem. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts
Published 2020“…The first objective of this thesis is to develop the run sum X - AI (RS X - AI) chart for monitoring the process mean. Optimal parameters computed using the optimization algorithms developed and the step-by-step approach for constructing the optimal RS - AI chart are provided in this thesis. …”
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15
Analytical Modelling And Efficiency Optimisation Of Permanent Magnet Synchronous Machine Using Particle Swarm Optimisation
Published 2018“…Subsequently, an intelligent computational algorithm - Particle Swarm Optimization (PSO) was later applied to all the machine variables simultaneously to find the optimal solution for a compromised optimal machine performance. …”
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Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…In the wake of fast soft computing processing, advances in hardware interface provisioning and demand over cost efficiency, a substantial acquiesce over the interests in nonlinear control and optimal process operation can been seen in recent academic and industrial study particularly in multivariable control processes. …”
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…In the wake of fast soft computing processing, advances in hardware interface provisioning and demand over cost efficiency, a substantial acquiesce over the interests in nonlinear control and optimal process operation can been seen in recent academic and industrial study particularly in multivariable control processes. …”
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19
Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…The proposed control algorithm takes advantage of a predefined Lyapunov control law which minimizes the required calculation time by the Lyapunov model equations just once in each control loop to predict future variables. …”
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20
A hybrid heuristic of variable neighbourhood descent and great deluge algorithm for efficient task scheduling in grid computing
Published 2019“…In this paper, we propose a novel hybrid heuristic-based algorithm, which synergised the excellent diversification capability of Great Deluge (GD) algorithm with the powerful systematic multi-neighbourhood search strategy captured in Variable Neighbourhood Descent (VND) algorithm, to efficiently schedule independent tasks in Grid computing environment with an objective of minimising the makespan. …”
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