Adsorption of ferrocyanide onto raw and acid-activated clinoptilolite and sepiolite: equilibrium modelling by error minimization

Clay Minerals ◽  
2013 ◽  
Vol 48 (4) ◽  
pp. 613-626 ◽  
Author(s):  
V. Önen ◽  
E. Yel
Keyword(s):  
Linear Models ◽  
Error Function ◽  
Linear Optimization ◽  
Error Minimization ◽  
Non Linear ◽  
Initial Adsorption ◽  
Adsorption Rates ◽  
Function Models ◽  
Best Fit ◽  
Modelling Approach

AbstractThe experimental data on adsorption of Fe and CN of a ferrocyanide complex onto raw and acid-activated clinoptilolite/sepiolite on the basis of detention time and particle size was modelled by a linear and a non-linear approach. The linearized best-fit isotherm selection method and non-linear error minimization was applied through Freundlich, Langmuir and Temkin isotherms. ERRSQ, MPSD, HYBRID and ARE error functions were minimized by a developed MATLAB script to determine the isotherm parameters in non-linear optimization. The complex was not adsorbed as whole anions but the Fe and CN were adsorbed separately. 0.65 mg Fe/L. min and 4.84 mg CN/L. min initial adsorption rates were achieved with acid activated clinoptilolite. The Fe adsorption was not as successful as CN. The adsorption of Fe and CN was described by Freundlich and Langmuir isotherms respectively. The differences between the predicted isotherm parameter sets of linear models and minimized error function models indicated that both the best-fit isotherm selection and the isotherm constant determinations can be performed properly by error minimization as well as by conventional linear best fit modelling approach.

Design Equations for Bod Removal in Facultative Ponds

1987 ◽  
Vol 19 (12) ◽  
pp. 187-193 ◽  
Author(s):  
E. Joe Middlebrooks
Keyword(s):  
Environmental Protection Agency ◽  
Linear Models ◽  
Plug Flow ◽  
Empirical Models ◽  
The Us ◽  
Non Linear ◽  
The Usa ◽  
Using Data ◽  
Removal Model ◽  
Best Fit

Facultative pond performance data collected for the US Environmental Protection Agency (USEPA) at four locations throughout the USA and data collected by others were used to evaluate the most frequently used design equations and to develop non-linear design equations. Empirical models were evaluated as well as the classical plug flow and complete mix models. The first order plug flow model gave the best fit of all the rational models. The empirical non-linear models did not fit the data, nor did the other empirical models with the exception being the areal loading and removal model. Attempts to verify the models developed with the USEPA data using data collected by others were not successful with the exception of the areal loading and removal model.

scholarly journals Estimation of annual compound growth rates of guava (Psidium guajava L.) fruit in Haryana using Non linear model

2019 ◽  
Vol 11 (4) ◽  
pp. 778-784
Author(s):  
Pardeep Panghal ◽  
Manoj Kumar ◽  
Sarita Rani
Keyword(s):  
Growth Rate ◽  
Linear Model ◽  
Growth Rates ◽  
Logistic Model ◽  
Linear Models ◽  
Psidium Guajava ◽  
Annual Growth Rate ◽  
Guava Fruit ◽  
Non Linear ◽  
Best Fit

Computation of growth rates plays an important role in agricultural and economic research to study growth pattern of a various commodities. Many of the research workers used the parametric approach for computation of annual growth rate but not use the concept of non-linear model.  In this paper, an attempt has been made to study growth rates of guava for three districts (Hisar, and Kurukshetra) and Haryana state as a whole using different non-linear models. The time series data on annual area and production of guava (Psidium guajava L.) in different districts of Haryana from 1990-91 to 2015-16 were collected to fit non linear models. Growth rates were computed through best fitted non-linear models. It was found that Logistic model could be best fit for computation of growth rates of area for guava fruit in Hisar and Kurukshetra district and Haryana state as a whole whereas Gompertz model was best fit for Yamunanagar district based on high R2 and least MSE and RMSE values. It was also observed that monomolecular model was best fit for production of guava fruits in Hisar and Yamunanagar district whereas Logistic model was best fit for production of guava fruit in Kurukshetra and Haryana state as a whole because of high R2 and least MSE and RMSE values. R and excel software have been used for fitting the non linear model and computation of growth rates for area and production of guava fruit for the year 1990-91 to 2015-16. None has been used the non linear model growth model for computation of annual growth rate of guava fruit for area and production of Haryana state. But in this work non linear growth model has been used for computation of growth rate instead of parametric approaches.

scholarly journals Are African Stock Markets Inefficient or Adaptive? Empirical Literature

2020 ◽  
Author(s):  
Adefemi A. Obalade ◽  
Paul-Francois Muzindutsi
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Linear Models ◽  
Empirical Studies ◽  
Weak Form ◽  
Empirical Literature ◽  
Recent Theory ◽  
Non Linear ◽  
Best Fit ◽  
Weak Form Efficiency

This chapter reviews empirical studies on weak form of efficiency with the aim of establishing whether the African market is inefficient or adaptive. The reviewed studies are categorised based on their methodological approaches to compare the power of linear and non-linear models in testing for weak-form efficiency. The studies on calendar anomalies, an indication of weak-form inefficiency, are reviewed to assess whether these anomalies are adaptive as portrayed by the relatively recent theory of adaptive market hypothesis (AMH). The scope of reviewed studies is also extended to developed and emerging markets to gain a broad comparison of the findings. This review revealed that non-linear dependence has been revealed in stock returns suggesting that non-linear models are best fit to test for the stock market efficiency. Reviewed studies produced contradictory findings with some supporting and others rejecting weak-form efficiency. Thus, most studies support the AMH, which suggests that market efficiencies and anomalies are time changing. This chapter concludes that most of the existing studies on AMH have been carried out in markets other than Africa, and hence, further empirical studies on the evolving and changing nature of efficiency in African stock markets are recommended.

scholarly journals Comparison of the parameters of the lactation curve between normal and difficult calvings in Iranian Holstein cows

2019 ◽  
Vol 17 (1) ◽  
pp. e0401
Author(s):  
Navid Ghavi Hossein-Zadeh
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Lactation Curve ◽  
Non Linear ◽  
Best Fit

To evaluate effect of dystocia on the lactation curve characteristics for milk yield and composition in Holstein cows, six non-linear models (Brody, Wood, Sikka, Nelder, Dijkstra and Rook) were fitted on 5,917,677 test day records for milk yield (MY), fat (FP) and protein (PP) percentages, fat to protein ratio (FPR) and somatic cell score (SCS) of 643,625 first lactation Holstein cows with normal calving or dystocia from 3146 herds which were collected by the Animal Breeding Center of Iran. The models were tested for goodness of fit using adjusted coefficient of determination, root means square error, Akaike’s information criterion and Bayesian information criterion. Rook model provided the best fit of the lactation curve for MY and SCS in normal and difficult calvers and dairy cows with dystocia for FP. Dijkstra model provided the best fit of the lactation curve for PP and FPR in normal and difficult calvers and dairy cows with normal calving for FP. Dairy cows with dystocia had generally lower 100-d, 200-d and 305-d cumulative milk yield compared with normal calvers. Time to the peak milk yield was observed later for difficult calvers (89 days in milk vs. 79 days in milk) with lower peak milk yield (31.45 kg vs. 31.88 kg) compared with normal calvers. Evaluation of the different non-linear models indicated that dystocia had important negative effects on milk yield and lactation curve characteristics in dairy cows and it should be reduced as much as possible in dairy herds.

scholarly journals Estimation of diurnal total radiation based on meteorological variables in the period of plant vegetation in Poland

2018 ◽  
Vol 23 ◽  
pp. 00032 ◽  
Author(s):  
Paulina Stanek ◽  
Leszek Kuchar ◽  
Irena Otop
Keyword(s):  
Relative Error ◽  
Linear Models ◽  
Meteorological Data ◽  
The Other ◽  
Meteorological Variables ◽  
Coefficient Of Determination ◽  
Total Radiation ◽  
Radiation Data ◽  
Non Linear ◽  
Best Fit

The paper presents selected models for the estimation of diurnal total radiation on the basis of other meteorological variables (using simple data as temperature and rainfall) in the vegetation months in the territory of Poland. For that purpose 6 meteorological stations were selected, having standard meteorological data as well as total radiation data for the period of 2001 – 2010. The stations were chosen so that two of them were situated on the coast, two in the lowland part of the country, and two in the mountains. The models were evaluated with the use of the coefficient of determination R² and the relative error of estimation RMSE with division into 6 months and 6 meteorological stations. In each of the regions the best results were obtained for models 6 and 7 which are combinations of the remaining models and additionally the constructed variable ΔT, used in other non-linear models analysed in the other studies. The best fit for those models was obtained for the mountain stations (R² from 0.67 to 0.75, RMSE from 2.7 to 4.4). The poorest estimation was obtained for the coastal stations (R² from 0.41 to 0.67, RMSE from 2.6 to 5.1). The paper does not indicate the best month in terms of the fitting, due to the high variation of results for the stations and the models.

scholarly journals Growth curves for Ile de France female sheep raised in feedlot

2016 ◽  
Vol 37 (1) ◽  
pp. 303 ◽  
Author(s):  
Raphael Patrick Moreira ◽  
Victor Breno Pedrosa ◽  
Paula Roberta Falcão ◽  
Michelli De Fátima Sieklicki ◽  
Caroline Gomes Rocha ◽  
...  
Keyword(s):  
Weight Gain ◽  
Negative Correlation ◽  
Linear Models ◽  
Growth Curves ◽  
Daily Weight Gain ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Non Linear ◽  
Best Fit ◽  
Female Sheep

The objective of the present study was to analize the non-linear models that best fit the growth of ewes Ile de France. The experiment was conducted in school farm Capão da Onça, located in city of Ponta Grossa - PR and so, were used data on weight at birth to 210 days of age of 34 females of the breed Ile de France. The animals showed mean weight at birth (PN) of 4,58 kilograms, weaning weight (P60) of 19,58 kilograms and weight at 210 days (P210) equal to 43,18 kilograms, providing daily weight gain (GMD) equal to 0,183 kg/day. The non-linear models used were: Brody, Von Bentarlanffy, Logístic and Gompertz, presenting results, respectively, of 33.5453; 33.7120; 33.6714 and 33.8836 for Error Mean Square (EMS) and 0.9650; 0.8302; 0.9649 and 0.9647 for coefficient of determination (R2). All models tended to describe accordingly the curve of animals growth, but, according to the methods adopted to select the most appropriate model, Von Bertarlanffy showed the best fit. All models presented high and negative correlation between the A and k parameters, indicating that the most precocious animals are less likely to reach elevated weights for 210 days of age

Predictive or Explanatory Models for Aquatic Ecosystems

1984 ◽  
Vol 16 (5-7) ◽  
pp. 571-578 ◽  
Author(s):  
S Gentil
Keyword(s):  
Computer Aided Design ◽  
Linear Models ◽  
Linear Optimization ◽  
Eutrophic Lake ◽  
Explanatory Models ◽  
Optimization Techniques ◽  
Non Linear ◽  
System Properties ◽  
Short Term Forecasting ◽  
Aided Design

This paper presents the modelling of a small eutrophic lake of the French Alps. A mechanistic non-linear model is elaborated; this model has to be simplified in view of its identifiability study, and parameters estimates are obtained by non-linear optimization techniques. The Computer-Aided-Design package known as I.S.E.R. has been used to develop linear models describing the phytoplankton or zooplankton data. These models prove useful to understand some system properties and are really efficient for short-term forecasting.

scholarly journals Determination of best-fit isotherm model for the sorption of Lead (II) and Manganese (II) ions onto acid-activated shale using selected non-linear error functions

2021 ◽  
Vol 5 (1) ◽  
pp. 11-19
Author(s):  
I. R. Ilaboya ◽  
J. S. Okpoko
Keyword(s):  
Standard Deviation ◽  
Error Function ◽  
Surface Characteristics ◽  
Isotherm Model ◽  
Isotherm Models ◽  
Error Functions ◽  
Function Computation ◽  
Normalized Error ◽  
Non Linear ◽  
Best Fit

The focus of this research is to apply the selected error function equation to establish the equilibrium isotherm model that best describes the adsorption of Pb2+ and Mn2+ onto acid-activated shale.  Data collected from the batch experiment were analyzed using selected isotherm models (Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Sips and Redlich-Peterson). To compute the isotherm parameters used in choosing the best-fit isotherm model, selected non-linear error functions, namely, error sum of the square, normalized standard deviation, hybrid error function, root mean square error and Marquardt’s percent standard deviation were employed. From the scanning electron microscope results, it was observed that the surface characteristics of the shale change considerably with calcination and acid treatment but the acid-treated shale shows better uneven porous surface characteristics. Error function computation shows that the Dubinin-Radushkevich isotherm model had the least sum of normalized error of 0.3623 for Pb2+ adsorption and 0.5465 for Mn2+ adsorption; hence, it was selected as the best isotherm model for explaining the sorption of Pb(II) and Mn(II) ions unto acid-activated shale.

G Optimal Design in Non linear Models to Increase Silicon Oxide Purity Levels and Electrical Conductivity

2018 ◽  
pp. 150-155
Author(s):  
Muklas Rivai
Keyword(s):  
Electrical Conductivity ◽  
Optimal Design ◽  
Linear Models ◽  
Silicon Oxide ◽  
Information Matrix ◽  
Relevant Information ◽  
Non Linear

Optimal design is a design which required in determining the points of variable factors that would be attempted to optimize the relevant information so that fulfilled the desired criteria. The optimal fulfillment criteria based on the information matrix of the selected model.

Sign in / Sign up

Export Citation Format

Share Document