Search Results - (( normal distribution means algorithm ) OR ( parameters evaluation force algorithm ))

Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

“…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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Calibration of optical based silicone tactile sensor based on image deformation technique / Abdul Halim Esa by Esa, Abdul Halim

“…Based on these three parameters, three different types of algorithm are developed in order to measure experimentally the forces and deformation based on optical information of the tactile sensor. …”
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Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm by Abdul Haris, Faranadia

“…Accordingly, the proposed Brute-Force search algorithm characterised the negative lightning return strokes parameters based on the seven parameters. …”
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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Pendulum-like algorithm as a local search technique by Abed I.A., Koh S.P., Sahari K.S.M., Tiong S.K., Younis H.A.-K., Abed A.A.

Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm by Ahmad Muinuddin, Mahmood, Zamri, Mohamed, Rosmazi, Rosli

“…The research aims to optimize key TMD parameters (mass ratio, damping ratio, and frequency ratio) using the dynamic CS algorithm. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

“…More specifically, we use multi-objective models that are the mean-entropy-entropy (MEE). The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Machine learning model to predict the contact of angle using mineralogy, TOC and process parameters in shale by Ameenuddin Irfan, S., Fadhli, M.Z., Padmanabhan, E.

“…A machine learning is needed to predict the contact angle in the shale using the process parameters and TOC and Minerology of the shale. Minerology and Total Organic Carbon (TOC) content are some of the important parameters to be evaluated for reservoir characterization. …”
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TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms by Marina, Patrick, Mah, Yau Seng, Putuhena, Frederik Josep, Wang, Yin Chai, Onni Suhaiza, Selaman

“…These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.…”
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Statistical approach on grading the student achievement via normal mixture modeling by Md. Desa, Zairul Nor Deana, Mohamad, Ismail, Mohd. Khalid, Zarina, Md. Zin, Hanafiah

“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali by Dali, Nur Izzaty

“…Pre-fire and post-fire of Landsat 7 ETM+ images were obtained to identify the fire severity using Normalized Burn Ratio algorithms. The objectives of this study are (1) to produce Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Soil Adjusted Vegetation Index (SAVI) and (2) to determine the changes of forest distribution based on NDVI, NBR and SAVI changes. …”
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A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

“…However, Z-Score Normalization, sometimes referred to as Standardization, standardizes the data by dividing by the standard deviation and subtracting the mean, maintaining the shape of the distribution and making it resistant to outliers. …”
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Statistical approach on grading the student achievement via mixture modelling by Md. Desa, Zairul Nor Deana, Mohamad, lsmail

“…In the conditional Bayesian model, we assume the Normal Mixture distribution where the grades are distinctively separated means and proportions of the Normal Mixture distribution. …”
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Crowd behavior monitoring using self-adaptive social force model by Wan Nur Azhani, W. Samsudin, Kamarul Hawari, Ghazali

“…The current method used is Social Force Model (SFM), which can describe the behavior of a crowd based on the interaction forces between individuals. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…These algorithms are data-driven and do not require thresholds or predefined assumptions. …”
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Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

“…Climate models; Flood control; Floods; Forecasting; Information management; Inverse problems; Mean square error; Multilayer neural networks; Multilayers; Normal distribution; Particle swarm optimization (PSO); Reservoir management; Reservoirs (water); Risk management; Rivers; Stream flow; Uncertainty analysis; Bat algorithms; Bayesian model averaging; Bayesian modelling; Copula bayesian model; Gamma test; Inclusive multiple model; Multilayers perceptrons; Multiple-modeling; Natural hazard; Optimization algorithms; Bayesian networks; flood; flood control; North Atlantic Oscillation; perception; reservoir; streamflow; uncertainty analysis; Kelantan; Malaysia; West Malaysia…”

Evaluation of different control policies of semi-active MR fluid damper of a quarter-car model by Rahman, Mahmudur, Rashid, Muhammad Mahbubur, Abdul Muthalif, Asan Gani, Kasemi, Banna

“…The main objective of this study is to evaluate performances of these control algorithms.…”
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Hardware-in-the-loop study of a hybrid active force control scheme of an upper-limb exoskeleton for passive stroke rehabilitation by Anwar, P. P. Abdul Majeed

“…A hardware-in-the-loop simulation is carried out to evaluate the appropriate gains of both the PD and the AFC inertial parameter gained that is tuned via the SKF algorithm. …”
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