scholarly journals Methods for Developing Models in a Fuzzy Environment of Reactor and Hydrotreating Furnace of a Catalytic Reforming Unit

2021 ◽  
Vol 11 (18) ◽  
pp. 8317
Author(s):  
Batyr Orazbayev ◽  
Ainur Zhumadillayeva ◽  
Kulman Orazbayeva ◽  
Lyailya Kurmangaziyeva ◽  
Kanagat Dyussekeyev ◽  
...  
Keyword(s):  
Parametric Identification ◽  
Fuzzy Regression ◽  
Regression Equations ◽  
Optimal Temperature ◽  
Catalytic Reforming ◽  
Nonlinear Regression Models ◽  
Modified Method ◽  
Fuzzy Environment ◽  
Comparison Results ◽  
Rule Bases

Methods for the development of fuzzy and linguistic models of technological objects, which are characterized by the fuzzy output parameters and linguistic values of the input and output parameters of the object are proposed. The hydrotreating unit of the catalytic reforming unit was investigated and described. On the basis of experimental and statistical data and fuzzy information from experts and using the proposed methods, mathematical models of a hydrotreating reactor and a hydrotreating furnace were developed. To determine the volume of production from the outlet of the reactor and furnace, nonlinear regression models were built, and fuzzy models were developed in the form of fuzzy regression equations to determine the quality indicators of the hydrotreating unit—the hydrogenated product. To identify the structure of the models, the ideas of sequential inclusion regressors are used, and for parametric identification, a modified method of least squares is used, adapted to work in a fuzzy environment. To determine the optimal temperature of the hydrotreating process on the basis of expert information and logical rules of conditional conclusions, rule bases are built. The constructed rule bases for determining the optimal temperature of the hydrotreating process depending on the thermal stability of the feedstock and the pressure in the hydrotreating furnace are implemented using the Fuzzy Logic Toolbox application of the MatLab package. Comparison results of data obtained with the known models, developed models and real, experimental data from the hydrotreating unit of the reforming unit are presented and the effectiveness of the proposed approach to modeling is shown.

A Study Relationship between Firm Performance and Dividend Policy by Fuzzy Regression: Iranian scenario

2013 ◽  
Vol 3 (2) ◽  
pp. 70
Author(s):  
Seyed Hasan Salehnezhad
Keyword(s):  
Regression Analysis ◽  
Stock Returns ◽  
Dividend Policy ◽  
Functional Relationship ◽  
Stock Exchange ◽  
Negative Relationship ◽  
Decision Makers ◽  
Fuzzy Regression ◽  
Independent Variables ◽  
Fuzzy Environment

Fuzzy regression analysis is an extension of the classical regression analysis that is used in evaluating the functional relationship between the dependent and independent variables in a fuzzy environment. Accounting dividend is the most important information used by decision makers in the economic analysis. This research investigated corporate governance and dividend policy in listed company's Tehran Stock exchange by fuzzy regression during 2010 and 2012. The results indicated that significant and positive relationship exists between financial performance (stock returns) and dividend policy and also there was a significant and negative relationship exists between economic performance (EVA) and dividend policy. Furthermore, a significant relationship exists between controlling variable (size) and dividend policy.

Fuzzy Statistics Approach for Aviation GTE Condition Estimation Technique

2006 ◽  
Author(s):  
P. S. Abdullayev
Keyword(s):  
Linear Models ◽  
Least Squares Method ◽  
Early Stage ◽  
Technical Condition ◽  
Multiple Correlation Coefficient ◽  
Fuzzy Regression ◽  
Recursive Least Squares ◽  
Regression Equations ◽  
Adequate Model ◽  
Skewness And Kurtosis

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients’ changes. Researches of skewness and kurtosis coefficients values’ changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes’ dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines’ technical condition. Researches of correlation coefficients values’ changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and nonlinear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Optimal temperature conditions in catalytic reforming reactors

1981 ◽  
Vol 17 (3) ◽  
pp. 121-124
Author(s):  
Yu. A. Skipin ◽  
A. P. Fedorov ◽  
G. N. Maslyanskii ◽  
E. A. Shkuratova
Keyword(s):  
Optimal Temperature ◽  
Catalytic Reforming ◽  
Temperature Conditions

scholarly journals Моделювання залежностей «багатовимірний вхід–вихід» для автоматизації процесів керування в умовах невизначеності

2015 ◽  
pp. 86-90
Author(s):  
Л. І. Лєві
Keyword(s):  
Least Squares Method ◽  
Statistical Processing ◽  
Fuzzy Regression ◽  
Regression Equations ◽  
Continuous Output ◽  
Fuzzy Regression Model ◽  
Multivariate Dependence ◽  
Input Variables ◽  
Definition Of

Розглянута у роботі технологія дає змогу шляхомпоєднання переваг м’яких обчислень і реґресійного ана-лізу будувати багатофакторні залежності з неперерв-ним виходом, враховуючи як можливість визначенняступеня важливості вхідних змінних, так і їх взаємодійнеобхідного порядку. Проте під час моделюванняоб’єктів із неперервним виходом, коли необхідна до-статня точність визначення чіткого значення вихідноївеличини, знаходження параметрів нечіткого рівнянняреґресії за методом найменших квадратів та парамет-рів функцій належностей шляхом статистичної оброб-ки експертної інформації не може в повній мірі забез-печити потрібну точність. Для цього потрібно налаш-тувати за навчальною вибіркою нечітку реґресійну мо-дель у відповідності до тестуючої вибірки. In work considered technology allows to build multivariate dependence with continuous output by combining the advantages of soft computing and regression analysis, given the opportunity, the definition of importance of input variables and their necessary interactions. However, when modeling objects with continuous output when a sufficient accuracy of the determination of a precise value of the output value is necessary, the identification of the parameters of fuzzy regression equations using the least squares method and parameters of membership functions by statistical processing of expert information is not sufficient to provide the desired accuracy. It requires configuration on the training set of a fuzzy regression model in accordance with the testing sample.

An Evaluation of a Buffered Agar Method for the Assay of Neomycin Sulfate in Feeds

1972 ◽  
Vol 55 (5) ◽  
pp. 1088-1091
Author(s):  
B J Williams ◽  
H J Mayerhofer
Keyword(s):  
Calcium Chloride ◽  
Linear Correlation ◽  
Regression Equations ◽  
Modified Method ◽  
Aoac Method ◽  
Neomycin Sulfate ◽  
The Mean ◽  
Agar Method ◽  
Commercial Feeds ◽  
Mean Concentration

Abstract The AOAC method for the assay of neomycin sulfate in feeds, 38.192–38.195, was modified by buffering the base and seed agar at pH 8.0 with tris (hydroxymethyl) aminomethane and deleting calcium chloride from the medium. Commercial feeds were assayed by both the modified and official AOAC methods and results were compared. The modified method was 2.64 times more sensitive than the AOAC method. The mean concentration of neomycin sulfate estimated by the modified method was 119.7% of that estimated by the AOAC method (significant at p < 0.01). Differences in method variability were not statistically significant at the 1% level. Linear correlation between the logarithms of neomycin concentrations and zone diameters was excellent for both methods, and the slopes of their regression equations were approximately equal.

scholarly journals Aircraft Gas Turbine Engines’ Technical Condition Identification System

2005 ◽  
Author(s):  
P. S. Abdullayev ◽  
A. M. Pashayev ◽  
D. D. Askerov ◽  
R. A. Sadiqov
Keyword(s):  
Gas Turbine ◽  
Least Squares Method ◽  
Technical Condition ◽  
Fuzzy Regression ◽  
Recursive Least Squares ◽  
Identification System ◽  
Regression Equations ◽  
Adequate Model ◽  
Non Linear ◽  
Skewness And Kurtosis

In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients’ changes. Researches of skewness and kurtosis coefficients values’ changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes’ dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines’ technical condition. Researches of correlation coefficients values’ changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine D-30KU-154 technical condition was made.

scholarly journals A Multicenter Study to Evaluate Harmonization of Assays for C-Terminal Telopeptides of Type I Collagen (ß-CTX): A Report from the IFCC-IOF Committee for Bone Metabolism (C-BM)

2021 ◽  
Author(s):  
E. Cavalier ◽  
◽  
R. Eastell ◽  
N. R. Jørgensen ◽  
K. Makris ◽  
...  
Keyword(s):  
Multicenter Study ◽  
Evaluation Method ◽  
Type I Collagen ◽  
Clinical Laboratory ◽  
Type I ◽  
Regression Equations ◽  
Long Term Storage ◽  
Comparison Results ◽  
The Difference ◽  
Routine Clinical Laboratory

Abstract Background Biochemical bone turnover markers are useful tools to assess bone remodeling. C-terminal telopeptide of type I collagen (ß-CTX) has been recommended as a reference marker for bone resorption in research studies. Methods We describe the results of a multicenter study for routine clinical laboratory assays for ß-CTX in serum and plasma. Four centers (Athens GR, Copenhagen DK, Liege BE and Sheffield UK) collected serum and plasma (EDTA) samples from 796 patients presenting to osteoporosis clinics. Specimens were analyzed in duplicate with each of the available routine clinical laboratory methods according to the manufacturers’ instructions. Passing-Bablok regressions, Bland–Altman plots, V-shape evaluation method, and Concordance correlation coefficient for ß-CTX values between serum and plasma specimens and between methods were used to determine the agreement between results. A generalized linear model was employed to identify possible variables that affected the relationship between the methods. Two pools of serum were finally prepared and sent to the four centers to be measured in 5-plicates on 5 consecutive days with the different methods. Results We identified significant variations between methods and between centers although comparison results were generally more consistent in plasma compared to serum. We developed univariate linear regression equations to predict Roche Elecsys®, IDS-iSYS, or IDS ELISA ß-CTX results from any other assay and a multivariable model including the site of analysis, the age, and weight of the patient. The coefficients of determination (R2) increased from approximately 0.80 in the univariate model to approximately 0.90 in the multivariable one, with the site of analysis being the major contributing factor. Results observed on the pools also suggest that long-term storage could explain the difference observed with the different methods on serum. Conclusion Our results show large within- and between-assay variation for ß-CTX measurement, particularly in serum. Stability of the analyte could be one of the explanations. More studies should be undertaken to overcome this problem. Until harmonization is achieved, we recommend measuring ß-CTX by the same assay on EDTA plasma, especially for research purposes in large pharmacological trials where samples can be stored for long periods before they are assayed.

scholarly journals PROBLEM OF DECISION-MAKING ON CONTROL OF THE PROCESS OF HYDRAULIC TREATMENT OF A CATALYTIC REFORMING PLANT IN A FUZZY MEDIUM AND DEVELOPMENT OF A METHOD FOR ITS SOLUTION

2021 ◽  
Vol 82 (4) ◽  
pp. 158-167
Author(s):  
B. Orazbaev ◽  
◽  
A. Zhumadillayeva ◽  
A. Tanirbergenova ◽  
K. Orazbayeva ◽  
...  
Keyword(s):  
Decision Making ◽  
Mathematical Formulation ◽  
Heuristic Method ◽  
Operating Mode ◽  
Catalytic Reforming ◽  
Initial Information ◽  
Fuzzy Environment ◽  
Manufactured Products ◽  
Decision Making Problem ◽  
Made In

The problems of formulating and solving the problem of making decisions on the control of the hydrotreating process in a fuzzy environment are investigated and an effective method for solving such problems with the involvement of experts, their experience, knowledge and intuition is proposed. The statement of the problem of controlling the hydrotreating process, which takes place in the hydrotreating reactor and is characterized by the indistinctness of the initial information, is obtained in the form of the problem of making decisions on the choice of the optimal operating mode of the hydrotreating reactor. The management criteria were chosen to maximize the volume of production, i.e. hydrogenate, and improving the quality characteristics of the manufactured products. In the mathematical formulation of the decision-making problem for the management of the hydrotreating process in a fuzzy environment and the development of a method for its solution, the ideas of the principle of the main criterion and maximin were used by adapting them to work in a fuzzy environment. A heuristic method has been developed for solving the assigned decision-making tasks for controlling the hydrotreating process in a fuzzy environment. The originality and novelty of the applied approach to the formulation and solution of the decision-making problem in a fuzzy environment consists in increasing the adequacy of the decision made in a fuzzy environment due to the maximum use of the initial fuzzy information.

scholarly journals Complex T-Spherical Fuzzy Aggregation Operators with Application to Multi-Attribute Decision Making

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1311 ◽  
Author(s):  
Zeeshan Ali ◽  
Tahir Mahmood ◽  
Miin-Shen Yang
Keyword(s):  
Decision Making ◽  
Aggregation Operators ◽  
Weighted Averaging ◽  
The Novel ◽  
Fuzzy Environment ◽  
Novel Approach ◽  
Operational Laws ◽  
Comparison Results ◽  
Fuzzy Aggregation ◽  
Multi Attribute Decision Making

In this paper, the novel approach of complex T-spherical fuzzy sets (CTSFSs) and their operational laws are explored and also verified with the help of examples. CTSFS composes the grade of truth, abstinence, and falsity with a condition that the sum of q-power of the real part (also for imaginary part) of the truth, abstinence, and falsity grades cannot be exceeded from a unit interval. Additionally, to examine the interrelationships among the complex T-spherical fuzzy numbers (CTSFNs), we propose two aggregation operators, called complex T-spherical fuzzy weighted averaging (CTSFWA) and complex T-spherical fuzzy weighted geometric (CTSFWG) operators. A multi-attribute decision making (MADM) problem is resolved based on CTSFNs by using the proposed CTSFWA and CTSFWG operators. To examine the proficiency and reliability of the explored works, we use an example to make comparisons between the proposed operators and some existing operators. Based on the comparison results, the proposed CTSFWA and CTSFWG operators are well suited in the fuzzy environment with legitimacy and prevalence by contrasting other existing operators.

Sign in / Sign up

Export Citation Format

Share Document