Results 41 to 50 of about 6,285,273 (279)

Modern techniques in variance estimation with auxiliary information: a logarithmic perspective

Arab Journal of Basic and Applied Sciences
Variance estimation is essential to statistical analysis because it sheds light on the accuracy and dependability of estimations. The effectiveness of traditional methods is frequently increased by using linear connections between the study and auxiliary
Poonam Singh, Prayas Sharma, Anjali Singh, Anamika Kumari   +3 more
doaj   +1 more source

Determination of Optimum Smoothing Constant of Single Exponential Smoothing Method: A Case Study [PDF]

International Journal of Research in Industrial Engineering, 2017
Exponential smoothing is a sophisticated forecasting method that works based on previous forecast plus a percentage of the forecast error. A key issue of this technique is the proper choice of exponential smoothing constant.
C. L. Karmaker
doaj   +1 more source

Dielectric Permittivity Tensor of Muscovite for Next Generation All Van Der Waals Broadband Photonic Components

Advanced Optical Materials, EarlyView.
Low‐index and low‐loss vdW muscovite represents an emerging robust dielectric platform for the creation of next‐generation all‐vdW nanophotonic architectures. Its utilization as a low‐index building‐block in all‐vdW multilayers enables extreme optical contrast when paired with MoS2, paving the way to the realization of few‐layer ultrathin DBS ...
Meri H. Hayrapetyan, Maksim L. Sargsyan, Davit A. Karakhanyan, Ani P. Khachatryan, Maria A. Levonyan, Dmitrii Litvinov, Maciej Koperski, Artsruni V. Margaryan, Makars Šiškins, Konstantin S. Novoselov, Davit A. Ghazaryan   +10 more
wiley   +1 more source

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

Elliptical Orbits Mode Application for Approximation of Fuel Volume Change

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2022
This article discusses the Elliptical Orbits Mode (EOM) as a method of approximating the function of changing the volume of fuel in the Underground Yank (UT). This research was conducted at the 45.507.21 Candirejo Tuntang Pertamina Gas Station.
Jovian Dian Pratama, Ratna Herdiana, Susilo Hariyanto   +2 more
doaj   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods.

PLoS ONE
This research compared the efficiency of several adjusted missing value imputation methods in multiple regression analysis. The four imputation methods were the following: regression-ratio quartile1,3 (R-RQ1,3) imputation of Al-Omari, Jemain and Ibrahim;
Juthaphorn Sinsomboonthong, Saichon Sinsomboonthong   +1 more
doaj   +1 more source

A steady-state analysis of the ε-normalized sign-error least mean square (NSLMS) adaptive algorithm

, 2011
In this work, expressions are derived for the steady-state excess-mean-square error (EMSE) of the ε-normalized sign-error least mean square (NSLMS) adaptive algorithm for both cases of real- and complex-valued data.
Zerguine, A., Ulla Faiz, M., Mohammed Mujahid Ulla Faiz, Azzedine Zerguine   +3 more
core   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting.

PLoS ONE
Demand forecasting is a quite challenging task, which is sensitive to several factors such as endogenous and exogenous parameters. In the context of supply chain management, demand forecasting aids to optimize the resources effectively.
Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola   +3 more
doaj   +1 more source