An approach to solving the problem of machining time estimation in production of complex products within CNC machining systems is presented in the paper. Heuristic analysis of the process is used to define the attributes of influence to machining time. For the problem of estimating machining time the following „Neural Computing techniques“ are used: Back-Propagation Neural Network, Modular Neur...

The paper evaluates by means of Monte Carlo simulations the estimator of the regression coefficient obtained by the classical W-based spatial autoregressive model and the structural equations model with latent variables (SEM) on the basis of data sets that contain two types of spatial dependence: spillover from (i) a hotspot and (iia) first order queen contiguity neighbors or (iib) inverse dist...

Medium spatial resolution biomass is a crucial link from the plot to regional and global scales. Although remote-sensing data-based methods have become a primary approach in estimating forest above ground biomass (AGB), many difficulties remain in data resources and prediction approaches. Each kind of sensor type and prediction method has its own merits and limitations. To select the proper est...

Seven empirical models and the artificial neural network model (ANN) are applied and validated to estimate the daily and monthly global solar radiation on a horizontal surface in Qena, Upper Egypt. Statistical comparison has been done between all these models. The results demonstrated that ANN model with MBE, RMSE, MPE, R, NSE and t values of -0.0692, 0.5338, 0.2647, 0.9946, 0.9890 and 2.4934 r...

OBJECTIVE To develop and cross-validate predictive models for percentage body fat (%BF) from anthropometric measurements [including BMI z-score (zBMI) and calf circumference (CC)] excluding skinfold thickness. METHODS A descriptive study was carried out in 3,084 pre-pubertal children. Regression models and neural network were developed with %BF measured by Bioelectrical Impedance Analysis (BI...

Biomass estimates are required for reporting carbon, assessing feedstock availability, and assessing forest fire threat. We developed diameterand height-based biomass equations for Western hemlock (Tsuga heterophylla (Raf.) Sarg.) and red alder (Alnus rubra Bong.) trees in Western Oregon. A system of component biomass equations was fitted simultaneously with a constrained seemingly unrelated re...

This study developed a retrieval algorithm for reflected shortwave radiation at the top of the atmosphere (RSR). This algorithm is based on Himawari-8/AHI (Advanced Himawari Imager) whose sensor characteristics and observation area are similar to the next-generation Geostationary Korea Multi-Purpose Satellite/Advanced Meteorological Imager (GK-2A/AMI). This algorithm converts the radiance into ...

__ Neural Network Model (NNM), Hidden Markov Model (HMM) and Regression Model (RM) are developed to predict the spread of dengue outbreak in Malaysia. The case study covered dengue cases data from Selangor, which include seven mukims and eight administrative districts in year of 2004 and 2005. Specific criteria concerned are location, time (weeks) and intensity of dengue cases. Critical discuss...

Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 (51Cr) EDTA excretion measurements (51Cr-EDTA ...