Results 51 to 60 of about 6,946,449 (205)

Convergence of Monte Carlo simulations involving the mean-reverting square root process [PDF]

, 2005
The mean-reverting square root process is a stochastic differential equation (SDE) that has found considerable use as a model for volatility, interest rate, and other financial quantities.
Mao, X., Higham, D.J.
core   +3 more sources

Improving the Near-Surface Wind Forecast around the Turpan Basin of the Northwest China by Using the WRF_TopoWind Model

Atmosphere, 2021
Wind energy is a type of renewable and clean energy which has attracted more and more attention all over the world. The Northwest China is a region with the most abundant wind energy not only in China, but also in the whole world.
Hui Ma, Xiaolei Ma, Shengwei Mei, Fei Wang, Yanwei Jing   +4 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

The root-mean-square error (RMSE) for effect of cell distribution and cell lag on the model fit to experimental data (cells/cm²).

, 2018
The root-mean-square error (RMSE) for effect of cell distribution and cell lag on the model fit to experimental data (cells/cm2).
William B. Lott (206536), Michael J. Osiecki (837098), Sean D. L. McElwain (5687690)   +2 more
core   +1 more source

Root-Mean-Square-Error (RMSE) of registration.

, 2022
RMSE of the point cloud registration, Eq (1), averaged over 10 different time frames and for all possible slab locations as functions of slab thickness for 1mm and 2.5mm slice thicknesses of moving slabs of scaphoid, capitate, and lunate.
Kevin M. Koch (10210935), Volkan Emre Arpinar (12732960), L. Tugan Muftuler (12732963), Mohammad Zarenia (12732957), Andrew S. Nencka (8468613)   +4 more
core   +1 more source

DENSE IMAGE MATCHING FOR MARS EXPRESS HRSC IMAGERY BASED ON PRECISE POINT PREDICTION METHOD [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
Currently, Mars Express HRSC imagery is an essential data source to derive high accuracy Mars topographic data. In view of the characteristics of Martian surface satellite imagery, a dense image matching scheme for HRSC imagery based on precise point ...
X. Geng, Q. Xu, J. Miao, Y. F. Hou, S. Xing, C. Z. Lan   +5 more
doaj   +1 more source

“Smart agriculture: a climate-driven approach to modelling and forecasting fall armyworm populations in maize using machine learning algorithms”

Frontiers in Plant Science
The fall armyworm (Spodoptera frugiperda) poses a significant threat to global maize production owing to its rapid life cycle, extensive host range, and strong dispersal capabilities. We developed a forecasting system for fall armyworm outbreaks over one
Vani Sree Kalisetti, Upendhar Sudharshanam, Nagesh Kumar Mallela Venkata, Rajashekhar Mandla, Srinivas Akula, Mallaiah Bedika, Bhadru Dharavath, Sreelatha Dogga, Ramakrishna Babu A, Chandrasekhar Javaji   +9 more
doaj   +1 more source

Comparison of errors generated by different similarity selection thresholds under the same experimental conditions (mean absolute error and root mean square error on MovieLens with selected users).

, 2022
Comparison of errors generated by different similarity selection thresholds under the same experimental conditions (mean absolute error and root mean square error on MovieLens with selected users).
Zhong Huang (358974), Jun Ai (519264), Fengyu Zhao (1781143), Zhan Su (264040), Lihui Shang (13170630), Xuanxiong Zhang (1976809)   +5 more
core   +1 more source

A general formula for calculating surface area of the similarly shaped leaves: Evidence from six Magnoliaceae species

Global Ecology and Conservation, 2020
Leaf area is an important indicator of photosynthetic capacity in plants. Knowledge of the variation of leaf shape at an individual level or a population level can help by accurately calculate leaf area.
Jiayan He, Gadi V.P. Reddy, Mengdi Liu, Peijian Shi   +3 more
doaj   +1 more source

Root mean square predicted error for RW1 models under Priors 1 & 2.

, 2015
Root mean square predicted error for RW1 models under Priors 1 & 2.
Margaret R. Donald (819862), Kerrie L. Mengersen (819863), Rick R. Young (819864)   +2 more
core   +1 more source