Search Results - (( parameter optimization approach algorithm ) OR ( data normalization based algorithm ))
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1
An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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2
Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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3
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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4
Estimating Crack Effects on Electrical Characteristics of PV Modules Based on Monitoring Data and I-V Curves
Published 2024“…Meanwhile, an innovative parameter optimization algorithm based on particle swarm optimization is developed to extract the parameters. …”
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5
Optimization of solenoid driver and controller for gaseous fuel high-pressure direct injector using model-based approach
Published 2022“…An optimization study was conducted using Normal Boundary Intersection (NBI) algorithm in MATLAB Model-Based Calibration (MBC) Toolbox to produce an optimal injector setup. …”
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6
The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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7
Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant
Published 2009“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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8
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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9
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The earlier intelligent approach presented an offline approach using only faulty line parameters for intelligent classifier model training to detect, classify and locate faults. …”
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10
Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes
Published 2025“…Six popular ML algorithms of regression, kernel and neural network-based models were applied to predict the gas-phase CO2 photoconversion rate. …”
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11
Spatiotemporal extraction of aquaculture ponds under complex surface conditions based on deep learning and remote sensing indices
Published 2025“…The CWI approach is implemented based on three index algorithms of remote sensing analysis such as the Water Index (WI), the Modified Normalized Difference Water Index (MNDWI) and the Automated Water Extraction Index with Shadow (AWEIsh). …”
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12
Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem
Published 2020“…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
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13
An expert integrative approach for sediment load simulation in a tropical watershed.
Published 2013“…Based on error analysis, differences between various scenarios in terms of error metrics were trivial, especially during the testing process. …”
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14
PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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15
Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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16
Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference
Published 2018“…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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17
Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
Published 2013“…Effects such as normality treatment, definition of neighbourhoods and weights and choice of autocorrelation parameter and parameter estimation are some of the complexities that are inherent to these models. …”
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18
Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
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Student Project -
19
Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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20
Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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