Search Results - (( data optimization modified algorithm ) OR ( parameter simulation model algorithm ))
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…Using an autoregressive moving (ARMA) model whose AR parameters are determined by solving high-order Yule-Walker equations (HOYWE) via the singular value decomposition (SVD) algorithm can alleviate this shortcoming. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…When the differences between the observed performance data and simulated data are found, the iterations are made to modify the accuracy of the match. …”
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Final Year Project -
5
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…Thus, an integrated simulation module consisting of an inverse optimization method and a finite element method was developed for modeling the powder compaction process as a whole. …”
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Enhanced multi-hop mechanism in vehicular communication system using swarm algorithm
Published 2021“…The paper aims to design a broadcast control system which is able to optimize the broadcast process in VANET. Vehicular network is modelled in Simulation of Urban Mobility (SUMO) and the algorithm is formulated in MATLAB. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The study simulated single-input-single-output (SISO) models: ARX and NARX. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…While the baseline model achieves 88 accuracy on Data1 and 97.6 on Data2, the proposed ALS-IOAP-DNN4 model attains perfect accuracy (100) on both datasets, demonstrating the effectiveness of ALS and advanced optimization techniques. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Assisted History Matching by Using Recursive Least Square and Discrete Cosine Transform
Published 2014“…In order to achieve the objective, a number of steps have been done. First, a synthetic model has been built by modifying ODEH data. Two sets of permeability value have been selected to get two data which are historical and simulated data from the model. …”
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Final Year Project -
16
Performance of amidoxime-modified poly(acrylonitrile- Co-acrylic acid) for removal of boron in aqueous solution
Published 2019“…Meanwhile, the Artificial Neural Network (ANN) was simulated from experimental data and applied to optimize, develop and create prediction models for boron adsorption by AO-modified poly(AN-co-AA). …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
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Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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Green retrofitting of building using BIM-based sustainability optimization
Published 2024“…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani
Published 2018“…To obtain the unknown vector of parameters of the MHTan, three heuristic optimization algorithms are employed to minimize the sum of squared residuals. …”
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