Search Results - (( process identification method algorithm ) OR ( parameter evaluation method algorithm ))
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1
Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA)
Published 2024“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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2
RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…The learning method will determine the performance’s capability of the networks for the system identification process which will be one of the key issues to be discussed in the thesis. …”
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Thesis -
3
Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…System identification is a method to build a model for a dynamic system from the experimental data. …”
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4
An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity
Published 2018“…Nonetheless, the outcomes of these research are particular in term of the assessed stages of classification conduit, the adopted data for assessments, and in the comparative baseline methods. The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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Proceeding -
5
Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi
Published 2018“…Secondly, in this research, an empirical dynamic model of the PEM fuel cell system in vehicles was analyzed and validated using the system identification method……”
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Book Section -
6
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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7
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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8
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…A major drawback of using the SEF function lies in its theoretical nature such that for a finite integration limit, the SEF become non-elementary integral and requires infinite series or numerical methods for evaluation. In addition,the identification of the exact SEF parameter used to scale the strength of saturation nonlinearity becomes impractical. …”
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9
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The algorithm searches the solution space by selecting various model structures and evaluating its fitness. …”
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Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review
Published 2022“…Objective: This article aims to evaluate current artificial intelligence applications and discuss their performance concerning the algorithm architecture used in forensic odontology. …”
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12
RLF and TS fuzzy model identification of indoor thermal comfort based on PMV/PPD
Published 2023“…This modeling is achieved using a Takagi-Sugeno (TS) fuzzy model and tuned by Gauss-Newton method for nonlinear regression (GNMNR) algorithm. …”
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13
Neural network based adaptive pid controller for shell-and-tube heat exchanger
Published 2019“…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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Student Project -
14
Neural network based adaptive pid controller for shell-and-tube heat exchanger: article
Published 2019“…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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15
Image segmentation method for boundary detection of breast thermography using random walkers
Published 2013“…The performance of the proposed method was evaluated by a board of three professional radiologists and the final decision was based on the majority agreement. …”
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Thesis -
16
Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…So,this optimization method can help to save time and cost of the process. …”
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Thesis -
17
A study on model-free approach for liquid slosh suppression based on stochastic approximation
“…In particular, we develop our own liquid slosh model from the input-output data of real plant through the system identification method. Then, the proposed model-free PID based SPSA is applied to the developed model. …”
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Research Report -
18
Development of data-driven controller for slosh suppression in liquid cargo vehicles
“…In particular, we develop our own liquid slosh model from the input-output data of real plant through the system identification method. Then, the proposed data-driven PID based SED is applied to the developed model. …”
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Research Report -
19
Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
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Thesis -
20
Detection of sweetness level for fruits (watermelon) with machine learning
Published 2020“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. …”
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Proceeding Paper
