Search Results - (( parameter estimation using algorithm ) OR ( parameter applying learning algorithm ))
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.]
Published 2021“…Two groups were formed and used as input to four machine learning algorithms. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning
Published 2024“…The FOSMC parameters are set by the ANN algorithm and then adapted through reinforcement learning to enhance the results. …”
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Tchebichef moment based restoration of Gaussian blurred images
Published 2016“…The estimated blur parameters from the proposed method are used in the split Bregman-based image restoration algorithm. …”
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Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation
Published 2020“…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
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The effect of human learning and forgetting on fuzzy EOQ model with backorders / Nima Kazemi
Published 2017“…Fuzzy set theory has been used to model inventory parameters subject to uncertainty, where determining uncertain parameters depends upon the subjective opinions of the decision makers. …”
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…The algorithms were implemented with optimized tuning parameters and validated with real-life porosity and permeability datasets obtained from diverse and heterogeneous petroleum reservoirs after they have passed on testing them with a benchmark dataset from the UCI Machine Learning Repository. …”
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Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil
Published 2021“…To obtain the best combination of these approaches for a good green building pricing model, it is important to identify what require extensive empirical experiments to work with identifying the best parameter configurations, techniques, and algorithms. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur...
Published 2012“…There is no existing tool to assist faculties in estimating the number of students that can achieve the objective, hence a prediction model using Backpropagation Algorithm is proposed by using a case study of UiTM Bandaraya Melaka Bachelor of Administrative Science students. …”
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Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete
Published 2022“…Therefore, sophisticated ML approaches are applied in this study to predict the compressive strength of steel fiber reinforced HSC (SFRHSC). …”
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State of charge estimation for electric vehicles using random forest
Published 2024“…The electric mobility landscape is rapidly evolving, demanding more precise SOC estimation methods to improve range prediction accuracy and battery management. This study applies a Random Forest (RF) machine learning algorithm to improve SOC estimation. …”
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Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD
Published 2014“…The method employs the ABC technique to learn the parameters of the adaptive thresholding function required for optimum enhancement. …”
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Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib
Published 2012“…Each signal was characterized by applying Nonlinear ARX (NARX) model and weight parameters of each disease were estimated. …”
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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“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction
Published 2013“…Second part has been done by proposing a novel learning rule containing genetic algorithm, Levenberg-Marquardt technique and least square estimation. …”
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