scholarly journals Analysis of Filtration Process Influence on the Results of Thermal Imaging Control of the Subsurface Defect’s Geometry in Solving Control Problems of Collaborative Robotic Systems

2021 ◽  
Vol 2096 (1) ◽  
pp. 012198
Author(s):  
S V Bushuev ◽  
E V Romash ◽  
O S Bashevskaya
Keyword(s):  
Error Estimation ◽  
Thermal Imaging ◽  
Control Program ◽  
Absolute Error ◽  
Robotic Systems ◽  
Confidence Probability ◽  
Control Problems ◽  
Filtration Process ◽  
Filtration Method ◽  
Linear Dimensions

Abstract The paper proposes and experimentally verifies an approach for estimating the thermal imaging error depending from the method of the subsurface defect’s linear dimensions filtering for forming the appropriate commands of the control program in a collaborative robotic system. The results are presented for the absolute error estimation depending on the filtration method with a confidence probability p=0,9972.

scholarly journals Alometric Model for Estimation of Leaf Area of Garcinia brasiliensis Mart. Through Non-destructive Method

2019 ◽  
Vol 11 (10) ◽  
pp. 154
Author(s):  
Vinicius de Souza Oliveira ◽  
Cássio Francisco Moreira de Carvalho ◽  
Juliany Morosini França ◽  
Flávia Barreto Pinto ◽  
Karina Tiemi Hassuda dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Linear Equations ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Maximum Width ◽  
Linear Dimensions ◽  
Length Width ◽  
Independent Variable ◽  
The Mean ◽  
Non Destructive

The objective of the present study was to test and establish mathematical models to estimate the leaf area of Garcinia brasiliensis Mart. through linear dimensions of the length, width and product of both measurements. In this way, 500 leaves of trees with age between 4 and 6 years were collected from all the cardinal points of the plant in the municipality of São Mateus, North of the State of Espírito Santo, Brazil. The length (L) along the main midrib, the maximum width (W), the product of the length with the width (LW) and the observed leaf area (OLA) were obtained for all leaves. From these measurements were adjusted linear equations of first degree, quadratic and power, in which OLA was used as dependent variable as function of L, W and LW as independent variable. For the validation, the values of L, W and LW of 100 random leaves were substituted in the equations generated in the modeling, thus obtaining the estimated leaf area (ELA). The values of the means of ELA and OLA were tested by Student’s t test 5% of probability. The mean absolute error (MAE), root mean square error (RMSE) and Willmott’s index d for all proposed models were also determined. The choice of the best model was based on the non significant values in the comparison of the means of ELA and OLA, values of MAE and RMSE closer to zero and value of the index d and coefficient of determination (R2) close to unity. The equation that best estimates leaf area of Garcinia brasiliensis Mart. in a way non-destructive is the power model represented by por ELA = 0.7470(LW)0.9842 and R2 = 0.9949.

scholarly journals Approach to implementation of local navigation of mobile robotic systems in agriculture with the aid of radio modules

2020 ◽  
Vol 12 (2) ◽  
pp. 92-97
Author(s):  
Roman Iakovlev ◽  
Anton Saveliev
Keyword(s):  
Wireless Networks ◽  
Unmanned Aerial Vehicles ◽  
Data Transfer ◽  
Absolute Error ◽  
Robotic Systems ◽  
Wireless Data ◽  
Mesh Topology ◽  
Task Distribution ◽  
Local Navigation ◽  
Algorithmic Model

In this paper an approach is presented, enabling to solve the problem of local navigation of mobile robotic platforms (MRP), based on utilization of wireless networks with mesh topology. Establishment of wireless networks was ensured, based on the set of radio modules, mounted on unmanned aerial vehicles (UAV), comprising a swarm. This paper presents a developed algorithm for establishment of such wireless networks, aided by LoRa-technology, as well as an algorithm for MRP localization, based on analysis of signal level, where the incoming signals are fed from MRP group radio modules to radio modules of wireless data transfer network. An algorithmic model is given for task distribution among UAV and to implement navigational capabilities of MRP swarm. In some experiments descending dependencies of absolute error value, pertinent to MRP, from the number of UAV in action were revealed, as well as of averaged deflection value of MRP positions in motion along their paths from the number of UAV in action. Thereby the averaged value of MRP localization error, depending on the number of UAV in action, was from 8.14 to 17.13 m, and the averaged value of MRP position deflection - from 16.38 to 57.12 m, respectively.

scholarly journals Combined Artificial Intelligence and Fuzzy logic Model for the process of groundwater treatment for irrigation and drinking purposes using filtration and other membrane process

2021 ◽  
Vol 945 (1) ◽  
pp. 012040
Author(s):  
S Narendran ◽  
Bhaskar Rao Yakkala ◽  
J Cyril Robinson Azariah ◽  
A Sivagami
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Research Work ◽  
Physical Parameters ◽  
Membrane Process ◽  
Fuzzy Logic Systems ◽  
Filtration Process ◽  
Sand Filter ◽  
Filtration Method ◽  
Double Filtration

Abstract The process of water purification or water filtration takes several stage approaches. In which, the membrane model process is an important role in filtration. This research work is done by considering double filtration method for filtration process and it is modelled by clustering of Artificial Neural Network and multiple linear regression approach. In this research work, ten different physical parameters and chemical parameters for designing our model. The measurement of groundwater quality for both irrigation and drinking water is a complex process due to various factors such as geology, hydrogeology, biology, etc. With the help of Neural network and fuzzy logic systems approach, we have studied the quality of water in various part of south India. For the process of double filtration process, we have taken rapid sand filter followed by slow sand filter. For the membrane process of water treatment, the membrane chosen for the research are reverse osmosis, microfiltration and nanofiltration.

scholarly journals A Comparison of Ordinary Least Squares and Least Absolute Error Estimation

1988 ◽  
Vol 4 (3) ◽  
pp. 517-527 ◽  
Author(s):  
Andrew A. Weiss
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Error Estimation ◽  
Method Of Moments ◽  
Linear Regression Model ◽  
Generalized Method Of Moments ◽  
Absolute Error ◽  
Ordinary Least Squares ◽  
Hausman Test ◽  
Heteroscedastic Errors

In a linear-regression model with heteroscedastic errors, we consider two tests: a Hausman test comparing the ordinary least squares (OLS) and least absolute error (LAE) estimators and a test based on the signs of the errors from OLS. It turns out that these are related by the well-known equivalence between Hausman and the generalized method of moments tests. Particular cases, including homoscedasticity and asymmetry in the errors, are discussed.

scholarly journals Estimation of Leaf Area by Linear Dimensions in Coffea dewevrei

2019 ◽  
pp. 1-8
Author(s):  
Omar Schmildt ◽  
Enilton Nascimento de Santana ◽  
Vinicius de Souza Oliveira ◽  
Rafael Ruy Gouvea ◽  
Lucas Corrêa Souza ◽  
...  
Keyword(s):  
Leaf Area ◽  
Technical Assistance ◽  
Absolute Error ◽  
Equation Model ◽  
Quadratic Model ◽  
Linear Dimensions ◽  
Independent Variable ◽  
Student’S T ◽  
Simple Linear Equation ◽  
The City

The objective of this research was to select the equation that best estimates the leaf area of the coffee tree Coffea dewevrei, from the linear dimensions of the leaves. For this purpose, 140 leaves of adult plants were collected from the Capixaba Institute for Research, Technical Assistance and Rural Extension, in the city of Linhares, North of the State of Espírito Santo, Brazil. The length (L), the width (W), the product of the multiplication between the length and width (LW) and the leaf area observed (OLA) were determined from all leaves. For the modeling, a 100 leaves sample was used, where OLA was used as a dependent variable in function of L, W and LW as independent variable, being obtained the following models: linear first degree, quadratic and power. For the validation, a sample of 40 leaves was used, where the values of L, W LW were substituted in the equations generated in the modeling, thus obtaining the estimated leaf area (ELA). A simple linear equation model was fitted for each modeling equation relating ELA in function of OLA. The hypotheses H0: β0 = 0 versus Ha: β0 ≠ 0 and H0: β1 = 1 versus Ha: β1 ≠ 1, were tested using Student's t test at 5% probability. The mean absolute error (MAE), root mean square error (RMSE) and Willmott's index d for all equations were also determined. The best model that estimates the area of Coffea dewevrei was chosen through the following criteria: β0 not different from zero, β1 not different from one, MAE and RMSE values closer to zero and index d closer to the unit. The area of the leaves can be determined by its greater width (W), through the quadratic model equation ELA=-10.255+1.020(W)+1.293(W)2.

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