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1
Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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2
Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms
Published 2022“…We use a number of experimental findings to show how well the suggested method performs.…”
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Proceedings -
3
Stator resistance estimation of induction motor using genetic algorithm
Published 2012“…This project is about to design genetic algorithm estimator using MATLAB software, and builds an actual induction motor using Newcastle University Drives Simulation Library. …”
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Undergraduates Project Papers -
4
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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5
Severity Estimation of Plant Leaf Diseases Using Segmentation Method
Published 2020“…The best severity estimation algorithm and color space used to estimate the diseases severity of plant leaf is the combination of Fuzzy C-Means and YCbCr color space. …”
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6
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Conference or Workshop Item -
7
Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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Thesis -
8
Robust remote heart rate estimation from multiple asynchronous noisy channels using autoregressive model with Kalman filter
Published 2019“…Also, it indicates that our algorithm can be used for the online environment. Finally, the application of our algorithm in search and rescue scenarios using drones is considered and an experiment is conducted to investigate the algorithm's potential to be embedded in drones.…”
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9
A Fuzzy-Neural Approach for Estimation of Depth Map using Focus
Published 2011“…Then neural network is used to train the FIS. The training is done using back propagation algorithm in combination with the least squares method. …”
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10
An evaluation of optical flow algorithms for crowd analytics in surveillance system
Published 2017“…The improvement in computational efficiency and increasing interest in robust and accurate motion estimation algorithms lead to increase in the use of optical flow in crowd analytic applications. …”
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11
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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Thesis -
12
Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…In this study, two combinations, M1 and M2, with different input variables, were used to assess the model's accuracy, and the best-performing model for monthly SL estimation was identified. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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16
Parallel visualization approach of a 3D heart model
Published 2008“…The basis of this technique is that the location of an object is estimated using an estimation algorithm and the radio frequency (RF) fingerprint database as a reference. …”
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17
On time-domain OFDM channel estimation: Use of pilots correlation for digital video broadcasting (DVB) cable receiver
Published 2015“…In this method, a certain combination of positive and negative sub-pilot tones is used to generate the null carriers in each OFDM symbol. …”
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18
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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19
Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach
Published 2025“…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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