Journal articles on the topic 'Input-output analysis Mathematical models'
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Vaninsky, Alexander. "Structural change optimization in input-output models." Journal of Interdisciplinary Mathematics 12, no. 6 (December 2009): 839–61. http://dx.doi.org/10.1080/09720502.2009.10700668.
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El-Demerdash, Basma E., Assem A. Tharwat, and Ihab A. A. El-Khodary. "A Unified Mathematical Model for Stochastic Data Envelopment Analysis." International Journal of Service Science, Management, Engineering, and Technology 12, no. 1 (January 2021): 127–41. http://dx.doi.org/10.4018/ijssmet.2021010108.
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Efficiency measurement is one aspect of organizational performance that managers are usually interested in determining. Data envelopment analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about the efficiency and performance of organizations and all sorts of functionally similar, relatively autonomous operating units. DEA models are either with a constant rate of return (CRS) or variable return to scale (VRS). Furthermore, the models could be input-oriented or output-oriented. In many real-life applications, observations are usually random in nature; as a result, DEA efficiency measurement may be sensitive to such variations. The purpose of this study was to develop a unified stochastic DEA model that handles different natures of variables independently (random and deterministic) and can be adapted to model both input/output-oriented problems, whether it is CRS or VRS. The chance-constrained approach was adopted to handle the stochastic variables that exist in the model. The developed model is implemented through an illustrative example.
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Zheng, Kai, and Yisheng Liu. "Application of Mathematical Models in Economic Variable Input and Output Models under the Scientific Visualization." Computational Intelligence and Neuroscience 2022 (February 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/6269358.
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At present, with the development of society and economy, some new problems have emerged continuously. Among them, the more serious problem is that enterprises pay too much attention to economic benefits, which leads to problems in the development of many enterprises. Therefore, the problem caused by too much emphasis on economic benefits is one of the major economic problems. After this problem, our country’s economy began to focus on economic input and output in the subsequent development process. And, related personnel have also studied the economic input-output technology and model, which is an economic quantitative analysis method that has been widely used in various aspects of the economic field since its emergence. This paper firstly elaborates the theoretical knowledge involved, such as economic data, economic variables, and visualization techniques. Secondly it analyzes the application of scientific visualization techniques in the processing of economic variable data, which includes the techniques of preprocessing, mapping, drawing, and displaying the data. Finally, this paper investigates the application of mathematical models in economic variables input and output and the application of mathematical models in economic research, which can help us to better understand and use the knowledge of economics, thus providing strong support for solving practical problems. Also, this helps people to understand and grasp more about the macroarea, microaspect, and even the country as a whole.
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Imai, Jun-ichi, Hiroyuki Shioya, and Masahito Kurihara. "Modeling and Analysis of Genetic Algorithms Based on the Viewpoint of Mixture Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 7, no. 3 (October 20, 2003): 268–75. http://dx.doi.org/10.20965/jaciii.2003.p0268.
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Some mathematical models have been proposed for theoretical analyses of genetic algorithms (GAs). However, these works have limited their objects to a few kinds of GAs in order to formulate them accurately. In this paper, we regard a GA as an information source that generates input-output data. That is, we regard a population and its next population generated by the GA as input and output respectively. Then we model the GA by learning from these data. Since this method uses only the input-output relations of data and ignores interior structures, we can describe a variety of GAs in a common form, and analyze them from a new point of view. We use some mixture models for a representation of these input-output relations in this paper. By using a mixture model for modeling a GA, we can represent the GA system as a combination of some partial systems. In this paper, we treat two types of mixture models, and investigate how these models are effective for analyzing GAs through some numerical experiments.
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Deng, Wei. "The Analysis of Energy and Environmental Efficiency Based on Input-Output Model." Applied Mechanics and Materials 34-35 (October 2010): 1253–57. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1253.
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Input-output method can conveniently analyze energy consumption and environmental load for iron and steel enterprises. It can visually express production manufacturing statement and the consumption of energy and non-energy. Mathematical models are helpful for quantitative analysis and data handling. In addition, it’s useful to analyze main affected factors. Unit process energy consumption and steel ratio directly affect energy efficiency, which can be analyzed by e-p method.
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Shabani, Amir, Gholam Reza Faramarzi, Reza Farzipoor Saen, and Mohsen Khodakarami. "Simultaneous evaluation of efficiency, input effectiveness, and output effectiveness." Benchmarking: An International Journal 24, no. 7 (October 2, 2017): 1854–70. http://dx.doi.org/10.1108/bij-10-2015-0096.
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Purpose The purpose of this paper is to develop a data envelopment analysis (DEA) technique that simultaneously measures efficiency and effectiveness to provide a comprehensive appraisal of the productivity. Additionally, an algorithm is recommended to determine targets that are used for measuring effectiveness. Design/methodology/approach In this paper, for measuring productivity, a new methodology based on non-parametric mathematical DEA technique was presented. The proposed procedure is able to compute the efficiency input effectiveness, and output effectiveness, simultaneously. Findings By comparing with previous models, the authors’ proposed integrated model generates more detailed results and has more discriminating power. Originality/value To the best of the authors knowledge, there is not any study in which a non-parametric mathematical approach measures productivity through simultaneous combining of the effectiveness, including input effectiveness, and output effectiveness, and the efficiency.
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Vittal, B., Raju Nellutla, and M. Krishna Reddy. "Selection and Analysis of Input-Output Variables using Data Envelopment Analysis of Decision Making Units - Indian Private Sector Banks." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 119–27. http://dx.doi.org/10.35940/ijeat.e2674.0610521.
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In banking system the evaluation of productivity and performance is the key factor among the fundamental concepts in management. For identify the potential performance of a bank efficiency is the parameter to evaluate effective banking system. To measure the efficiency of a bank selection of appropriate inputoutput variables is one of the most vital issues. The suitable identification of input-output variables helps to create and identify model in order to evaluate the efficiency and analysis. The Data Envelopment Analysis (DEA) is a mathematical approach used to measure the efficiency of identified Decision Making Units (DMUs). The DEA is a methodology for evaluating the relative efficiency of peer decision making units of identified input/output variables for the financial year 2018-19. In this study the basic DEA CCR, BCC models used for measure the efficiency of DMUs. In addition to these models for minimize the input excess and output shortfall Slack Based Measure (SBM) efficiency used. The SBM is a scalar measure which directly deals with slacks of input, output variables which help in obtain improved efficiency score compare with previous model. The result from the analysis is
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Novotny, V., H. Jones, X. Feng, and A. Capodaglio. "Time Series Analysis Models of Activated Sludge Plants." Water Science and Technology 23, no. 4-6 (February 1, 1991): 1107–16. http://dx.doi.org/10.2166/wst.1991.0562.
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Time series models of the activated sludge process are very useful in design and real time operation of wastewater treatment systems which deal with variable influent flows and pollution loads. In contrast to common deterministic dynamic mathematical models which require knowledge of a large number of coefficients, the time series models can be developed from input and output monitoring data series. In order to avoid “black box” approaches, time series models can be made compatible and identical in principle, with their dynamic mass balance model equivalents. In fact, these two types of models may differ only in nomenclature. ARMA-Transfer Function models can be used for systems which are linear or can be linearized such as typical BOD or suspended solids influent-effluent relationships for which the type of model is known. For systems which are highly nonlinear, and/or the input-output model is unknown, neural network models can be used. Both ARMA-TF models and neural network models can be made self-learning, that is, the performance of the model can be periodically improved manually or in an automated mode as new information is collected by monitoring. Application examples are included.
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Emmenegger, J. F., D. Chable, H. A. Nour Eldin, and H. Knolle. "Sraffa and Leontief Revisited: Mathematical Methods and Models of a Circular Economy." Cybernetics and Computer Technologies, no. 2 (July 24, 2020): 86–99. http://dx.doi.org/10.34229/2707-451x.20.2.9.
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Introduction. Sometimes new results in one scientific field can help to study quite other branches. In the new book we observe application of various mathematical methods to study circular economics. The purpose of the paper is to give information about the new book “SRAFFA AND LEONTIEF REVISITED: Mathematical methods and models of a circular economy”. The academic editor Walter de Gruyter-Oldenbourg has published this monography in January 2020 in English language. Results. This book contributes to the increasing call for a comprehensive perception of economic production processes. The book is dedicated to Wassily Leontief’s concept of Input-Output Analysis and to Piero Sraffa's seminal book “Production of Commodities by Means of Commodities”. Single product and joint production industries of a circular economy are described, consequently using matrix algebra. The central role of the Perron-Frobenius Theorem for non-negative matrices, specially Perron-Frobenius eigenvalues and eigenvectors is revealed as a common basis of Sraffa’s and Leontief’s approaches and applied to clarify the basic economic assumptions which are inherent to economic production processes. Conclusions. The book addresses young researchers wishing to explore the foundations of circular economy, practitioners wishing to examine the potential of Sraffa’s price models in connection to Leontief’s Input-Output analysis. Advanced undergraduate, graduate, PhD students and their instructors in economics, political science or applied mathematics, who seek to understand Sraffa and the recent developments of the circular economy of inter industrial and national economy will find numerous examples with complete solutions, presented by a rich, formal, mathematical methodology, revealing the economic content of the results. Detailed examples and visualizing graphs are presented for applications of various mathematical methods. Keywords: Input-Output analysis, circular economy, Perron-Frobenius Theorem, non-negative matrix.
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Stetsyuk, Petro, Maria Grygorak, Oleg Berezovskyi, and Oleksii Lykhovyd. "Mathematical Models of M.V. Mykhalevych for Forecasting Structural and Technological Changes." Cybernetics and Computer Technologies, no. 3 (November 29, 2022): 56–66. http://dx.doi.org/10.34229/2707-451x.22.3.6.
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Introduction. The identification of structural and technological disproportions that affect crisis phenomena in the economy and the analysis of ways to eliminate them require a wide application of quantitative research methods, in particular, mathematical modeling. “Input-Output” tables of Leontief turned out to be quite a convenient tool for analyzing these economic issues. In Leontief-type models, the matrix of technical coefficients (matrix of direct costs) is assumed to be known and calculated on the basis of statistical information from the “input-output” tables. M.V. Mykhalevych formulated the “inverse” problem: how to determine those structural and technological changes that would reduce the cost of production and thereby increase the incomes of end consumers and make the economy more dynamic. Or, in other words, how to choose or adjust technical coefficients to improve the properties of the economic process. This work is devoted to two optimization problems built on the basis of models of this type. The purpose of the article is to optimize the interdisciplinary planning of structural and technological changes. Results. Inverse models of the Leontief type for optimization of structural and technological transformations in economic systems are considered. These models are formulated in terms of nonlinear programming problems and include two objective functions for maximization: total consumer incomes and the “income growth–production growth” multiplier. Algorithms and software for solving these problems are presented. Numerical optimization procedures are based on Shor's r-algorithm. Conclusions. The use of inverse models of the Leontief type will allow choosing promising directions of structural and technological transformations in both the macro- and microeconomy. The proposed mathematical apparatus based on non-smooth optimization algorithms proved to be a sufficiently effective tool for solving appropriate optimization problems in practice. Keywords: structural and technological changes, inter-industry balance, Leontief model, “input-output” matrix, inverse Leontief-type models, non-smooth optimization algorithms, software.
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Kutsenko, Oleksandr, and Serhii Kovalenko. "QUASI-ANALYTIC METHOD OF LINEAR DYNAMIC SYSTEMS INVERSION." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (8) (December 23, 2022): 45–50. http://dx.doi.org/10.20998/2079-0023.2022.02.07.
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The problem of inversion of dynamic systems has become widespread while solving the problems of control, identification, and measurement problems arising during the design and research of electrical and mechanical dynamic systems. Inverting is an effective way of implementing disturbance control processes, as well as in combined control systems with a predictive model. The analysis of information sources showed that in the practical solution of most inversion problems, a number of difficulties arise, which are associated with the high sensitivity of the results in relation to the accuracy of the parameters of the mathematical model of the control object, the instability of the inverse model of non-minimum-phase objects, and the violation of the conditions of physical feasibility. The work offers an effective method of inverting linear stationary dynamic systems, free from the mentioned shortcomings in many respects. The basis of the method is the presentation of input and output signals in the form of infinite linear combinations of their derivatives. A method of determining the sequence of matrix coefficients of linear representations of input and output signals is proposed. The main theoretical result is obtaining relationships between matrix coefficients of input and output signals. The work considers mathematical models of linear dynamic systems in the form of differential equations in the state space and in the equivalent "input-output" form. The considered systems must meet the conditions of asymptotic stability, as well as the condition of equal dimensions of the input and output vectors. Requirements for mathematical models of input and output signals are given, the fulfillment of which allows, instead of infinite sums representing signals, to be limited to a finite number of terms.
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Abdallah, Wafaa, Jacqueline Saliba, Ziubir-Mehdi Sbartaï, Marwan Sadek, Fadi Hage Chehade, and S. Mohammed ElAchachi. "Reliability analysis of non-destructive testing models within a probabilistic approach." MATEC Web of Conferences 281 (2019): 04003. http://dx.doi.org/10.1051/matecconf/201928104003.
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The diagnosis of reinforced concrete is essential to detect the degradation and thus maintain the structural performance of civil engineering structures. This paper aims to establish a mathematical relationship between the ultrasonic pulse velocity UPV (considered as an observable variable) and two concrete properties indicators (compressive strength fc and water content W) within a probabilistic framework. Synthetic simulations are proposed to derive a conversion model between the statistical properties of the output and the input parameters for a reinforced concrete structure by taking into account spatial variability of concrete.
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KURYSHEV, Nikolai I. "The problem of measuring the quantity of output in the input–output model by W. Leontief in modeling the trends in economic reproduction of nations and regions." Regional Economics: Theory and Practice 19, no. 8 (August 16, 2021): 1568–92. http://dx.doi.org/10.24891/re.19.8.1568.
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Subject. This article deals with the problem of constructing a Leontief's input–output matrix. Objectives. The article aims to determine the rules for constructing a Leontief's input–output matrix on the basis of data on production time and quantity of product output. Methods. For the study, I used the methods of logical and mathematical analyses. Results. The article formulates the rules for constructing a Leontief's input–output matrix, taking into account differences in the time of production, quantity of output, as well as the conditions for the reproduction of the resources expended. It summarizes these rules for the J. von Neumann model. Conclusions. The proposed approach to the analysis of the material mechanism of economic reproduction defines the relationship between the quantitative and cost characteristics of the production and consumption of products and resources. This relationship opens up new opportunities for the application of input–output models to create simple and accurate algorithms for identifying and predicting the macroeconomic trends.
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MODARRES, MOHAMMAD, EBRAHIM NASRABADI, and MOHAMMAD MEHDI NASRABADI. "FUZZY LINEAR REGRESSION ANALYSIS FROM THE POINT OF VIEW RISK." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 12, no. 05 (October 2004): 635–49. http://dx.doi.org/10.1142/s0218488504003120.
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In this paper, fuzzy linear regression models with fuzzy/crisp output, fuzzy/crisp input are considered. In this regard, we define risk-neutral, risk-averse and risk-seeking fuzzy linear regression models. In order to do that, two equality indices are applied to express the degree of equality between a pair of fuzzy numbers. We also develop three mathematical models to obtain the parameters of fuzzy linear regression models. Minimizing the difference between the total spread of the observed and estimated values is the objective of these models. The advantage of our proposed models is the simplicity in programming and computation.
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Jagathesan, Dr T. "A critical study of the evolution of Mathematics in Economic Analysis." JOURNAL OF DEVELOPMENT ECONOMICS AND MANAGEMENT RESEARCH STUDIES 08, no. 08 (2021): 78–82. http://dx.doi.org/10.53422/jdms.2021.8801.
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Mathematical economics is an electrifying division of study in economics. It is helpful in model building and provides mathematical form of a descriptive theory in a simple as well as easily understandable way. Economics axiomatization can be embedded with mathematical formula to make it more scientific. Some of the concepts and theories like input-output analysis, linear programming, theory of games and economic behaviour, economic problems of optimum allocation of resources, organizing and planning of production, hyper formalistic methods now the application of computer simulation, normative economics ideas into positive economics for testing its validity given the normative assumptions, and failure of some mathematical models. This paper discusses about the evolution of mathematical economics critically.
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Sowale, Ayodeji, and Athanasios J. Kolios. "Numerical Analysis of the Adiabatic and Quasi Steady Model of Free Piston Stirling Engine." MATEC Web of Conferences 198 (2018): 04005. http://dx.doi.org/10.1051/matecconf/201819804005.
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This study presents the numerical simulation of the adiabatic and Quasi steady models of the free piston Stirling engine, the mathematical equations are presented, and design parameters are determined and used as input for the simulation. The simulations are computed under adiabatic and Quasi operating conditions, and their output results are compared. The similarities and differences in the model predictions in terms of the pressure to volume diagram, the amplitudes of the pistons and displacer, temperature, efficiency, power output and stable operation are observed and investigated. The models are validated against the experimental output and the results show a good agreement with the experiment. The adiabatic model predicted an output power of 862 W, while Quasi steady model predicted more accurate output power of 997W at frequency of 30 Hz in relation to the 1000 W of the experimental output. The effects of the variation of engine’s parameters on the output power are also observed and presented.
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Pruski, Piotr, and Stefan Paszek. "Analysis of asymmetrical operating conditions of a power system for different models of synchronous generators." ITM Web of Conferences 28 (2019): 01004. http://dx.doi.org/10.1051/itmconf/20192801004.
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In the paper, the waveforms of the output quantities of different mathematical models of a synchronous generator operating in a power system (PS) are compared. In the investigations, it was assumed that the PS consisted of a generating unit (including, among others, a synchronous generator) connected to a bus by a high voltage transmission line. The disturbances of the steady state in the form of symmetrical and asymmetrical short-circuits in a selected place of the transmission line were considered. In the generator model, the subtransient asymmetry was taken into account. The XT and RL models of the synchronous generator when assuming different input and output quantities of the system were investigated.
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Kravtsov, A. "System analysis of friction and wear processes when using fullerene compositions in lubricants." Problems of tribology 101, no. 3 (September 30, 2021): 15–25. http://dx.doi.org/10.31891/2079-1372-2021-101-3-15-25.
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The system-structural approach in researches of processes of friction and wear at application of fullerene compositions in lubricants is proved in the work. It is proposed to use a multilevel approach to study and model the processes of deformation of the surface layers of movable and fixed triboelements and the formation on energy-activated surfaces of wear-resistant structures containing fullerene molecules. The essence of the approach is to use multi-scale research methods to build mathematical models within a single research structure. Due to the fact that tribosystems differ in the integrity of the interconnected elements included in them, it is assumed that all processes occur at three hierarchical levels. At this level, they interact with each other and exchange energy and matter. Input and output flows in studies of tribosystems are formulated. It is shown that the input streams include design parameters of the tribosystem, technological parameters, operating parameters. These parameters form the flow of matter, energy and information, which is the input effect on the tribosystem. The output flow from the tribosystem are the parameters: volumetric wear rate I, dimension m3/hour; friction losses, which are estimated by the coefficient of friction f, dimensionless quantity. The output stream is the information flow of the tribosystem. When solving contact problems, this allows to take into account not only the level of stresses, but also the speed of deformation in the materials of the surface layers, as well as the depth of deformation, which in the models will take into account the volume of deformed material.Depending on the tasks and requirements for their solution, the use of different methodological approaches for modeling is justified. It is shown that the application of mathematical models in the modeling of tribological processes depends on the correct choice of technical constraints that determine the range of optimal solutions
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Xia, Meimei. "Choquet-Integral-Based Data Envelopment Analysis with Stochastic Multicriteria Acceptability Analysis." Symmetry 14, no. 4 (March 22, 2022): 642. http://dx.doi.org/10.3390/sym14040642.
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Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiencies of decision-making units (DMUs) by using a set of inputs and a set of outputs. However, traditional DEA models always assume that the inputs or outputs are independent of each other, which is unrealistic in practical problems. To reflect the interactions between inputs or outputs, the Choquet integral is employed in DEA models. The traditional DEA models are usually used to find some specific input and output weights of DMUs to optimize the efficiency score of DMUs, but the corresponding input and output weights for the optimal efficiency score of a DMU may not be distributed symmetrically, that is to say, the space of weights may be different for different DMUs. Instead of finding the self-efficiency score and the cross-efficiency score of a DMU in traditional DEA models based on some specific input and output weights, stochastic multicriteria acceptability analysis is used to explore the input or output evaluation space and weight space to calculate the Choquet-integral-based acceptability indices of DMUs. The proposed method considers the interactions between inputs or outputs, which can make more DMUs efficient and can also measure the acceptability of a DMU to become an efficient one by exploring the supporting information space. Examples are given to illustrate the proposed method.
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Hassan, Abdul Kareem, Raad Jasim, and Yousif Ashoor. "Estimation of Submerged Arc Plates Weldment Properties Using ANFIS and Regression Techniques." Basrah journal for engineering science 20, no. 2 (2020): 27–33. http://dx.doi.org/10.33971/bjes.20.2.4.
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The present work aims to build mathematical models based on experimental data to estimate the mechanical properties of submerged arc weldment. AISI 1020 low carbon steel plates 16mm thickness were welded according to orthogonal array in order to establish the relationship between input parameters (welding current, Arc voltage and welding speed) and output parameters (ultimate tensile stress, yield stress, impact energy and hardness) by submerged arc welding (SAW) process. The relationship between input and output parameters for the welding process are conducted using two suitable mathematical models the first one based on regression analysis, while the second one based on multi input single output ANFIS model for estimation of some mechanical properties of the welded plates. It was found that ANFIS results are closer to the experimental results than regression results. The optimal parameters (which give a maximum value of ultimate tensile strength (UTS), yield stress and impact energy; 446 MPa, 318 MPa and 213 J) are welding current is (380 Amp), Arc voltage is (25 V) and welding speed is (40 cm/min), while the maximum value of hardness number is (228 HV), when current welding is (380 Amp), Arc voltage is (25 V) and welding speed is (25 cm/min).
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Haider, Zeeshan, Abasin Ulasyar, Abraiz Khattak, Haris Sheh Zad, Alsharef Mohammad, Ahmad Aziz Alahmadi, and Nasim Ullah. "Development and Analysis of a Novel High-Gain CUK Converter Using Voltage-Multiplier Units." Electronics 11, no. 17 (September 2, 2022): 2766. http://dx.doi.org/10.3390/electronics11172766.
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High conversion gain is often required for the grid integration of renewable energy resources such as PV, fuel cells, and wind. It is desired that the stress across switches is lower when higher voltage gain is attained. Similarly, it is also preferred that the converter can achieve high voltage gain without operating at higher duty cycle values. This article presents a novel high-gain CUK converter (HGCC) that uses voltage-multiplier units. The HGCC is a combination of a modified CUK converter and voltage-multiplier units (VMUs). The converter utilizes a boost converter as an input to the modified CUK converter, resulting in an increase in the gain value. The voltage gain of HGCC is increased further by placing VMUs. Based on its overall design, the HGCC inherits various advantages of the CUK converter, such as continuous input and output current, resulting in low input and output current ripples. A mathematical model is developed for the HGCC, which helps calculate its voltage gain at different stages. The model is developed considering ideal elements without conduction and switching losses. Generalized equations for output voltage and gain are derived for n level converter. A simulation study was performed in MATLAB/Simulink that further highlights the advantages of the HGCC. Voltage stresses across different components and the switching of MOSFET and diodes are studied in simulations. An experimental setup is established for hardware prototyping of the converter and validation with the simulation and Mathematical models.
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Singh, Sunpreet, Chander Prakash, Parvesh Antil, Rupinder Singh, Grzegorz Królczyk, and Catalin I. Pruncu. "Dimensionless Analysis for Investigating the Quality Characteristics of Aluminium Matrix Composites Prepared through Fused Deposition Modelling Assisted Investment Casting." Materials 12, no. 12 (June 13, 2019): 1907. http://dx.doi.org/10.3390/ma12121907.
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The aluminium matrix composites (AMCs) have become a tough competitor for various categories of metallic alloys, especially ferrous materials, owing to their tremendous servicing in the diversified application. In this work, additional efforts have been made to formulate a mathematical model, by using dimensionless analysis, able to predict the mechanical characteristics of the AMCs that have already been optimized and characterized by the authors. Here, the experimental and statistical data obtained from the Taguchi L18 orthogonal array and analysis of variance (ANOVA) have been used. They permit collection of the output responses and allow the identification of significant process parameters, respectively, which thereafter were used to design the mathematical model. Second order polynomial equations have been obtained from the specific output response and the relevant input parameter were incorporated with the highest level of contribution. The obtained quadratic equations indicate the regression values (R2) equal to unity, hence, proving the performances of the fit. The results demonstrate that the developed mathematical models present very high accuracy for predicting the output responses.
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Miraoui, Imed, Mohamed Boujelbene, and Mouna Zaied. "High-Power Laser Cutting of Steel Plates: Heat Affected Zone Analysis." Advances in Materials Science and Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/1242565.
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The thermal effect of CO2high-power laser cutting on cut surface of steel plates is investigated. The effect of the input laser cutting parameters on the melted zone depth (MZ), the heat affected zone depth (HAZ), and the microhardness beneath the cut surface is analyzed. A mathematical model is developed to relate the output process parameters to the input laser cutting parameters. Three input process parameters such as laser beam diameter, cutting speed, and laser power are investigated. Mathematical models for the melted zone and the heat affected zone depth are developed by using design of experiment approach (DOE). The results indicate that the input laser cutting parameters have major effect on melted zone, heat affected zone, and microhardness beneath cut surface. The MZ depth, the HAZ depth, and the microhardness beneath cut surface increase as laser power increases, but they decrease with increasing cutting speed. Laser beam diameter has a negligible effect on HAZ depth but it has a remarkable effect on MZ depth and HAZ microhardness. The melted zone depth and the heat affected zone depth can be reduced by increasing laser cutting speed and decreasing laser power and laser beam diameter.
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Lombard, C. "Four-Port Representations of Heat Exchangers." International Journal of Mechanical Engineering Education 26, no. 1 (January 1998): 1–10. http://dx.doi.org/10.1177/030641909802600102.
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Two-port models represent a subsystem as a black box with an input and an output port. They are very convenient mathematical representations of subsystems, allowing easy connection between subsystem models to form a larger model. From an educational point of view, two-ports emphasize the idea of a subsystem as part of a larger structure. In this paper the concept is applied to two-stream heat exchangers, which are represented by a four-port model: two input ports and two output ports. It provides a new method of heat exchanger analysis which is complementary to the usual LMTD and effectiveness methods. It is easy to comprehend and ideal for computer programming. Large networks of heat exchangers are easily solved. In addition, it allows approximate models for heat exchangers with nonconstant properties as a cascade of constant property elements.
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Ágreda Bastidas, Jesús Alberto, Juan Andrés Montoya Arguello, and Carolina Mejía. "Biological homochirality and stoichiometric network analysis: Variations on Frank’s model." Revista Colombiana de Química 50, no. 3 (June 29, 2022): 42–53. http://dx.doi.org/10.15446/rev.colomb.quim.v50n3.96921.
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Biological homochirality is modelled using chemical reaction mechanisms that include autocatalytic and inhibition reactions as well as input and output flows. From the mathematical point of view, the differential equations associated with those mechanisms have to exhibit bistability. The search for those bifurcations can be carried out using stoichiometric network analysis. This algorithm simplifies the mathematical analysis and can be implemented in a computer programme, which can help us to analyse chemical networks. However, regardless of the reduction to linear polynomials, which is made possible by this algorithm, in some cases, the complexity and length of the polynomials involved make the analysis unfeasible. This problem has been partially solved by extending the stoichiometric matrix with rows that code the duality relations between the different reactions occurring in the network given as input. All these facts allow us to analyse 28 different network models, highlighting the basic requirements needed by a chemical mechanism to have spontaneous mirror symmetry breaking.
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Olejnik, Adam. "The impact of parameters of air hyperbaric exposure on the decompression chamber first ventilation." Zeszyty Naukowe Akademii Marynarki Wojennej, no. 1 (March 31, 2017): 61–73. http://dx.doi.org/10.5604/0860889x.1237623.
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The material presents an analysis of the impact that the parameters of air hyperbaric exposure have on the time remaining to the beginning of the first ventilation, as calculated with two mathematical models. The research has been conducted in the form of simulations that take into account standard parameters of exposure. Differences between the analysed models have been indicated, and the influence of the changes of particular input values in the analysed models on the output values has been defined.
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Zakharchenko, Anastasiya, and Oleksandr Stepanets. "MATHEMATICAL MODELING OF THE FAN COIL TEMPERATURE BEHAVIOR." Bulletin of the National Technical University «KhPI» Series: New solutions in modern technologies, no. 3(13) (October 26, 2022): 11–17. http://dx.doi.org/10.20998/2413-4295.2022.03.02.
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Fan coils are widely used in heating and air conditioning systems in both residential buildings and commercial areas. This article deals with the creation of a mathematical model of the fan coil for use in control systems, building digital twins, etc. The development of models of components of building engineering systems contributes to the introduction of more sophisticated control algorithms and analytics to coordinate the operation of equipment and as a result improve the energy efficiency of systems, the ability to investigate the dynamics of systems, etc. In this paper, a system of heat balance equations for the water, air and walls of the heat exchanger was used, which allows for simulating the operation of the system in transient modes. Considerable attention was paid to the calculation of the coolant and air parameters, including specific heat capacity, heat transfer coefficients, water and air thermal conductivity, kinematic viscosity coefficients, density, etc. The use of dynamic calculation of the coolant and air characteristics was proposed, an algorithm using the Python programming language and the CoolProp, SciPy, and NumPy libraries were implemented, and simulation results were presented. To assess the effectiveness of the proposed solutions, an analysis of the simulation results for the system with constant values of the coolant and air parameters, determined from the averaged initial values of the input and output parameters of the model, compared to the system with dynamic calculation, was performed. Finally, we investigated the dynamics of the external factor influence on the simulation results and presented an analysis of the influence of the model input variables on the output temperature values due to implicit relationships in the calculation of the parameters characterizing the heat transfer fluid and the air in the fan coil. According to the results of the comparison, the deviations in the simulation results of the models under study were estimated for the calculated value of heat output on the air side in absolute and relative units.
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Sevvel, P., C. Satheesh, and R. Senthil Kumar. "Generation of regression models and multi-response optimization of friction stir welding technique parameters during the fabrication of AZ80A Mg alloy joints." Transactions of the Canadian Society for Mechanical Engineering 44, no. 2 (June 1, 2020): 311–24. http://dx.doi.org/10.1139/tcsme-2019-0162.
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Conventional methodologies employed for the selection of weld process parameters for fabricating sound quality weldments have been found to consume more time and are often unreliable. Therefore, in this paper, an analysis was made to develop a quadratic regression model and empirical relationships by employing response surface methodology between various input parameters of the friction stir welding (FSW) technique including rotational speed of tool, axial force, and traversing speed of tool and five responses of output including percentage of elongation, yield strength, tensile strength, grain size, and microhardness. The discrepancies between the anticipated values and the genuine experimental outcomes are within ±1%, which reveals that the established mathematical quadratic regression model was a good fit to the actual experimental results. The experimental analysis also determined the elite combination of input parameters of the FSW technique for the output parameters.
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Erdoğan, H., and E. Gülal. "Identification of dynamic systems using Multiple Input–Single Output (MISO) models." Nonlinear Analysis: Real World Applications 10, no. 2 (April 2009): 1183–96. http://dx.doi.org/10.1016/j.nonrwa.2007.12.008.
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Chandra, Moi Subhas, Rudrapati Ramesh, Pal Pradip Kumar, and Bandyopadhyay Asish. "Analysis of Impact Behaviour of TIG Weldment by Using Hybrid RSM and CSO." Strojnícky časopis - Journal of Mechanical Engineering 69, no. 4 (December 1, 2019): 105–14. http://dx.doi.org/10.2478/scjme-2019-0046.
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AbstractTungsten inert gas (TIG) welding is a multi-input and multi-output variant process. The input process parameters and other factors of welding process interact in a complicated manner and influence the weld quality – directly or indirectly. Keeping this in mind, the present work has been planned to study the impact behaviour of TIG weldment through experiments, analysis and optimization. Experimental runs have been considered as per Box-Behnken design of response surface methodology (RSM). Based on the recorded data, the mathematical models have been developed to study the effect of process parameters on impact strength. ANOVA has been utilized to identify the influence of input process parameters on the response i.e. impact strength. RSM and cuckoo search optimization (CSO) algorithm have also been applied to optimize the impact strength.
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Ebrahimnejad, Ali, Madjid Tavana, Seyed Hadi Nasseri, and Omid Gholami. "A New Method for Solving Dual DEA Problems with Fuzzy Stochastic Data." International Journal of Information Technology & Decision Making 18, no. 01 (January 2019): 147–70. http://dx.doi.org/10.1142/s0219622018500396.
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Data envelopment analysis (DEA) is a widely used mathematical programming technique for measuring the relative efficiency of decision-making units which consume multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally used in classical DEA models, real-life problems often involve uncertainties characterized by fuzzy and/or random input and output data. We present a new input-oriented dual DEA model with fuzzy and random input and output data and propose a deterministic equivalent model with linear constraints to solve the model. The main contributions of this paper are fourfold: (1) we extend the concept of a normal distribution for fuzzy stochastic variables and propose a DEA model for problems characterized by fuzzy stochastic variables; (2) we transform the proposed DEA model with fuzzy stochastic variables into a deterministic equivalent linear form; (3) the proposed model which is linear and always feasible can overcome the nonlinearity and infeasibility in the existing fuzzy stochastic DEA models; (4) we present a case study in the banking industry to exhibit the applicability of the proposed method and feasibility of the obtained solutions.
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Cicci, Ludovica, Stefania Fresca, Stefano Pagani, Andrea Manzoni, and Alfio Quarteroni. "Projection-based reduced order models for parameterized nonlinear time-dependent problems arising in cardiac mechanics." Mathematics in Engineering 5, no. 2 (2022): 1–38. http://dx.doi.org/10.3934/mine.2023026.
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<abstract><p>The numerical simulation of several virtual scenarios arising in cardiac mechanics poses a computational challenge that can be alleviated if traditional full-order models (FOMs) are replaced by reduced order models (ROMs). For example, in the case of problems involving a vector of input parameters related, e.g., to material coefficients, projection-based ROMs provide mathematically rigorous physics-driven surrogate ROMs. In this work we demonstrate how, once trained, ROMs yield extremely accurate predictions (according to a prescribed tolerance) – yet cheaper than the ones provided by FOMs – of the structural deformation of the left ventricular tissue over an entire heartbeat, and of related output quantities of interest, such as the pressure-volume loop, for any desired input parameter values within a prescribed parameter range. However, the construction of ROM approximations for time-dependent cardiac mechanics is not straightforward, because of the highly nonlinear and multiscale nature of the problem, and almost never addressed. Our approach relies on the reduced basis method for parameterized partial differential equations. This technique performs a Galerkin projection onto a low-dimensional space for the displacement variable; the reduced space is built from a set of solution snapshots – obtained for different input parameter values and time instances – of the high-fidelity FOM, through the proper orthogonal decomposition technique. Then, suitable hyper-reduction techniques, such as the Discrete Empirical Interpolation Method, are exploited to efficiently handle nonlinear and parameter-dependent terms. In this work we show how a fast and reliable approximation of the time-dependent cardiac mechanical model can be achieved by a projection-based ROM, taking into account both passive and active mechanics for the left ventricle providing all the building blocks of the methodology, and highlighting those challenging aspects that are still open.</p></abstract>
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Mayoufi, Abir, Stéphane Victor, Manel Chetoui, Rachid Malti, and Mohamed Aoun. "Output error MISO system identification using fractional models." Fractional Calculus and Applied Analysis 24, no. 5 (October 1, 2021): 1601–18. http://dx.doi.org/10.1515/fca-2021-0067.
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Abstract This paper deals with system identification for continuous-time multiple-input single-output (MISO) fractional differentiation models. An output error optimization algorithm is proposed for estimating all parameters, namely the coefficients and the differentiation orders. Given the high number of parameters to be estimated, the output error method can converge to a local minimum. Therefore, an initialization procedure is proposed to help the convergence to the optimum by using three variants of the algorithm. Moreover, a new definition of structured-commensurability (or S-commensurability) has been introduced to cope with the differentiation order estimation. First, a global S-commensurate order is estimated for all subsystems. Then, local S-commensurate orders are estimated (one for each subsystem). Finally the S-commensurability constraint being released, all differentiation orders are further adjusted. Estimating a global S-commensurate order greatly reduces the number of parameters and helps initializing the second variant, where local S-commensurate orders are estimated which, in turn, are used as a good initial hit for the last variant. It is known that such an initialization procedure progressively increases the number of parameters and provides good efficiency of the optimization algorithm. Monte Carlo simulation analysis are provided to evaluate the performances of this algorithm.
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Wu, Zhigang, Yangmin Li, and Min Hu. "Design and optimization of full decoupled micro/nano-positioning stage based on mathematical calculation." Mechanical Sciences 9, no. 2 (November 21, 2018): 417–29. http://dx.doi.org/10.5194/ms-9-417-2018.
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Abstract. Nano-positioning is widely used in Micro-electromechanical Systems (MEMS), micromanipulator and biomedicine, coupling errors and tiny output displacements are the main disadvantages of the one. A totally uncoupled micro/nano-positioning stage with lever amplifiers is designed and tested in this paper. It is fully symmetrical along with the x- and y-directions. For obtaining large output displacements, two fully symmetric two-stage lever displacement amplifiers are utilized to amplify output displacements of piezoelectric actuators (PZTs). The established models for performances evaluation of the stage, in terms of kinetostatics, amplification ratio, reachable workspace, the input and output stiffness, are verified by finite element analysis (FEA). After that, the dimensional optimization is also carried out through the genetic optimization algorithm.The prototype of the mechanism is fabricated by using Wire-Electrical-Discharge-Machining (WEDM) process. Testing results indicate that the proposed micromanipulator demonstrates good performance.
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Jing, Xing Peng. "Reservoir Pressure of Coal-Bed Methane Prediction Research Based on Analysis Method by Neural Net-Work." Advanced Materials Research 756-759 (September 2013): 4758–62. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.4758.
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In Order to Achieve Accurate Quantitative Results of Parameters for Reservoir Pressure of Coal-Bed Methane, Neural Network Prediction Analytic Method is Adopted to Predict the Reservoir Pressure of Coal-Bed Methane. the Main Controlling Factors such as Conformation Stress, Buried Depth, in-Situ Stress and Permeability are Investigated. Mathematical Models of Neural Network of Reservoir Pressure of Coal-Bed Methane of Mathematical Analysis and System Architecture are Established; Taking the Qinshui Basin Coal Seam as Example to Forecast and use Reservoir Pressure of Coal-Bed Methane. Projections Show that: the use of Neural Network Prediction of Reservoir Pressure of Coal-Bed Methane is Feasible; Neural Network Method Makes up a Mathematical Point of Linear and Regularity in Order to Solve the Non-Linear Complex Relationship between the Input and Output Parameter Variables.
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Klyuchko, O. M., and P. V. Beloshitsky. "Biosensor concept and data input to biomedical infornation systems." Medical Informatics and Engineering, no. 3 (June 10, 2021): 51–69. http://dx.doi.org/10.11603/mie.1996-1960.2020.3.11698.
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Background. In present publication we generalized and analyzed deeply the experience of some biosensors studying in biophysical experiments with aim to incorporate them further to electronic information systems. Output biosensor electrical signals were input ones to electronic information system making their connection into joined bioinformation system. Materials and methods. Methods of comparative analysis of the characteristics of input and output electrical information signals of biosensor were applied; its physical and mathematical models were developed. For biosensor properties studies the methods of transmembrane electric currents recording in voltage-clamp mode as well as patch-clamp on hippocampal neuronal membranes were used. Results. Biosensor concept and their general characteristic were given, corresponding prototypes were observed. The physical model of biosensor was developed and some test results of this device were suggested. The biosensor was examined as abstraction in consistent unity of its functions: signal receiver — filter — analyzer — encoder/decoder. A brief mathematical description of biosensor functioning was given as well as corresponding algorithm. As a result of performed works the possibilities of this biosensor incorporation to bioinformation electronic systems were substantiated and the example of such system «EcoIS» was observed. Conclusion. In conclusion following results of the works were summarized. The detailed description of technical devices — biosensors as elements of biomedical information systems were done as well as analysis of electrical information signals at output of biosensor, its ability to encode information and detailed analysis of the possibility to incorporate this biotechnical device into electronic information systems due to biosensor output electricals signals.
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Kuz’michev, Venedikt, Ilia Krupenich, Evgeny Filinov, and Yaroslav Ostapyuk. "Comparative Analysis of Mathematical Models for Turbofan Engine Weight Estimation." MATEC Web of Conferences 220 (2018): 03012. http://dx.doi.org/10.1051/matecconf/201822003012.
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Accurate mathematical models for turbofan engine weight estimation are necessary requirement for optimization of the working process parameters at the initial design stage. Open-access publications provide necessary information on eight models that may be used at this design stage. Information on 77 modern turbofan engines was gathered using the available sources: publications, official websites, reference books etc. Data gaps were filled using the mathematical model identification. Gathered data cover wide range of working process parameters, thrust levels and air flow rates and was used to assess the accuracy of the abovementioned weight models. Only four models (Torenbeek, Svoboda, Raymer, Kuz’michev) provide adequate accuracy. Kuz’michev model uses the highest number of input parameters and provide the most precise results, although it must be noted that no correlation between the number of input parameters and accuracy was determined in general.
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Toroptsev, E. L., A. S. Marakhovskii, and R. R. Duszynski. "The problem of digitalization of the dynamic input-output model." Economic Analysis: Theory and Practice 16, no. 5 (May 28, 2020): 946–72. http://dx.doi.org/10.24891/ea.19.5.946.
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Subject. The article addresses the digitalization of the dynamic model of inter industry balance. Objectives. We focus on developing our own statistical research base for input-output analysis, structural forecasting, sustainability, economic dynamics and economic growth. Mathematically, the study is formalized by the Cauchy problem for ordinary differential equations. Methods. The methodology components include theoretical and practical bases of the systems, statistical, input-output, and structural dynamic analysis. Results. Based on official statistics, we solved the problem of digitalization of the dynamic model of input-output balance, written in the form of a system of differential equations. For the first time, this model was transferred from a set of purely theoretical structures to a class of computable models. We developed a sequence of coordinated actions and calculations, which serve as a methodology for the said transfer. We also devised and presented the elements of our own statistical research base. Conclusions. The quantitative measurement of the dynamic inter-industry model in the form of a system of differential equations opens up broad perspectives on the sustainability of macroeconomics, its structural readiness for expanded reproduction, i.e. economic growth. The model can be used both independently and in combination with equilibrium and other agent-oriented models.
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Ибятов, Ravil Ibyatov, Шайхутдинов, Farit Shaykhutdinov, Валиев, and Abdulsamad Valiev. "MODERN METHODS AND APPROACHES OF INFORMATION PROCESSING OF SPRING WHEAT PRODUCTIVITY." Vestnik of Kazan State Agrarian University 11, no. 3 (October 31, 2016): 9–15. http://dx.doi.org/10.12737/22668.
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The productivity of spring wheat crops is the result of a complex interaction of many different factors. Construction of mathematical models, using modern methods and approaches, make it possible to explore and optimize the conditions of the environment in relation to the genetic program of a particular culture and thus increase crop productivity. We used the monitoring results of wheat yield for 32 years and eight major independent factors, affecting it: humidity, the effective temperature during the growing season, rainfall, vegetation period, gluten content, the weight of a thousand grains, grain weight from one ear, straw length. The factor analysis was used previously to improve the efficiency of the model. The use of this analysis led to reveal a latent correlation between factors, and group the data, thereby reducing the dimension of the problem. We obtain four main components (MC), corresponding a linear combination of factor loadings and factors, that describe the 83% of output factor dispersion. A part of dispersion, explained by MC1, is approximately 37%; MC2 - 21%, MC - 13% MC4 - 12%. Further investigation is to build and compare two mathematical models. The first classical model is deal with the construction of the regression equation and the second is a neural network research model, based on neural networks of multilayer perceptron type with one input, one output, and one hidden layer. The four major components are used as input parameters of the model. The models were tested on the input set and checked for adequacy of using Fisher’s exact test. As a result, both models showed good results, but more similar to the original data were the results of the neural network model.
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Stentsel, Yo I., and K. A. Litvinov. "Mathematical Models of Conservative Objects of Control." Metrology and instruments, no. 1 (March 2, 2020): 30–36. http://dx.doi.org/10.33955/2307-2180(1)2020.30-36.
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Trend analysis and record charts different technological parameter in the heat power, chemical and oil refining industry showed, that most of them are oscillatory in nature. In order to reduce the amplitude of the oscillations, filters are used, and for the actual value of the measured quantity — their average value. Research has found, that the oscillatory-pulse nature of trends and diagrams of measured values is observed in multi-parameter technological objects of control, which have valve valve strapping on both input and output material, heat or energy flows. It is shown that valve-type regulating organs, which are used in automatic control systems, together with the technological apparatus create partial objects, which work on a conservative type. This creates new dynamic objects with three or more private conservative systems, which together create a complex multi-parameter technological control object with the oscillatory-pulse nature of the measured parameters. It was found that in many cases for such complex objects of control the average value of the measured parameter, defined with the trend, can differ significantly from its actual value. This leads to the appearance of significant measurement errors, and consequently, to an incorrect assessment of the quality of manufactured products. The task is to study the causes of the appearance of such vibrational-pulse systems, their properties, deviations of average readings along the trend from the actual value of the measured parameter, and also develop methods for reducing measurement errors. The paper presents mathematical and physical models of such conservative control systems, obtained on the basis of the theory of rheological transformations, as well as the results of their research. It is shown that the vibrational-pulse trends of the measurement parameters are a set of angular frequencies of private objects, the sum of which creates an oscillatory-pulse form of the signals of the measuring parameters.
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Manohar, M., T. Selvaraj, D. Sivakumar, and Koshy M. George. "Modeling of Turning Parameters for Inconel 718 Alloy using ANN." Journal of Advanced Manufacturing Systems 14, no. 04 (September 29, 2015): 203–13. http://dx.doi.org/10.1142/s0219686715500134.
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For machining a component, it is important to understand the characteristics of work material in order to choose the appropriate cutting tool and to fix a set of machining parameters to achieve optimum output. Analytical models of machining processes require complete understanding of process mechanism and hence are difficult to be developed. Once developed, these models are useful in parametric optimization, process simulation, operation and process planning, process parameter selection, parametric analysis, process performance prediction, verification of the experimental results, and improving the process performance by implementing/incorporating the theoretical findings. Neural network models associated with artificial intelligence are known as artificial neural networks (ANNs) which are simple mathematical models in the form of defining a function. This work presents the details of the experiments carried out for data acquisition, method of building the ANN models and their validation. These models can be used for predicting the output for a chosen set of input variables or for a specific desired output, finding the set of input variables to be chosen. This work resulted in developing models for the turning process for Inconel 718 alloy in a scientific manner. It also enables further scope of identifying the optimized set of turning parameters for Inconel 718 material using the newly developed coated carbide tools, achieving quality surface and productivity.
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Shananin, Alexander A., and Anastasiya V. Rassokha. "Inverse problems in analysis of input-output model in the class of CES functions." Journal of Inverse and Ill-posed Problems 29, no. 2 (January 14, 2021): 305–16. http://dx.doi.org/10.1515/jiip-2020-0138.
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Abstract The article proposes a modification of the approach to the analysis of inter-industry balance. Instead of linear models of inter-industry balance, based on the hypothesis of W. Leontief about the constancy of the cost standards of production factors, the article studies nonlinear models. For the case of production functions with constant elasticity of substitution (CES) an algorithm for solving the inverse problem is proposed, which allows to identify the model of nonlinear inter-industry balance based on the data of the symmetric input-output table. Based on the Young transform and Fennel duality, with the help of this model, we develop a technology for analyzing inter-industry relationships. The technology has been tested on the data of economic statistics of Russia.
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Nhan, TRAN Huu, NGUYEN Ngoc Thanh, VO Ba Khanh Trinh, and NGUYEN Van Nguyen. "Dynamic analysis of small gasoline car model powertrain using MATLAB / SIMDRIVELINE." Science & Technology Development Journal - Engineering and Technology 3, SI2 (April 15, 2021): first. http://dx.doi.org/10.32508/stdjet.v3isi2.575.
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The powertrain model of a vehicle using a small gasoline engine is designed based on the analysis results of the Matlab/Simdriveline simulation model. In which, the vehicle's powertrain model parts include: engine, clutch, gearbox, differential and wheels, and overall vehicle modeled by Matlab/ Simdriveline. Mathematical basis of the corresponding models for systems or components are used to build simulated models for the entire vehicle's powertrain system. The input parameters for the simulation problem include parameters of the size, mass, structural and technical parameters of each system such as transmission ratio, power, velocity, efficiency, determined based on actual vehicle model and empirical calculations. The simulation calculation process is done on the basis of the variation of the engine power, from which, the corresponding input and output kinetic and dynamic parameters of each system in the powertrain system consists of clutch, gearbox, differential, are obtained in the time domain. The results of simulation calculation of the kinematics and dynamics of each system in the vehicle's powertrain are analyzed as a basis for design improvement to improve the dynamic performance of the vehicle model.
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Ghattas, Omar, and Karen Willcox. "Learning physics-based models from data: perspectives from inverse problems and model reduction." Acta Numerica 30 (May 2021): 445–554. http://dx.doi.org/10.1017/s0962492921000064.
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This article addresses the inference of physics models from data, from the perspectives of inverse problems and model reduction. These fields develop formulations that integrate data into physics-based models while exploiting the fact that many mathematical models of natural and engineered systems exhibit an intrinsically low-dimensional solution manifold. In inverse problems, we seek to infer uncertain components of the inputs from observations of the outputs, while in model reduction we seek low-dimensional models that explicitly capture the salient features of the input–output map through approximation in a low-dimensional subspace. In both cases, the result is a predictive model that reflects data-driven learning yet deeply embeds the underlying physics, and thus can be used for design, control and decision-making, often with quantified uncertainties. We highlight recent developments in scalable and efficient algorithms for inverse problems and model reduction governed by large-scale models in the form of partial differential equations. Several illustrative applications to large-scale complex problems across different domains of science and engineering are provided.
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VASILEIOU, EVANGELOS. "ACCURACY VERSUS COMPLEXITY TRADE-OFF IN VaR MODELING: COULD TECHNICAL ANALYSIS BE A SOLUTION?" Journal of Financial Management, Markets and Institutions 07, no. 02 (October 22, 2019): 1950003. http://dx.doi.org/10.1142/s2282717x19500038.
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Accurate Value at Risk (VaR) estimations are crucial for the robustness and stability of a financial system. Even though significant advances have been made in the field of risk modeling, many crises have emerged during the same period, and an explanation for this is that the advanced models are not widely applied in the financial industry due to their mathematical complexity. In contrast to the mathematically complex models that torture the data in the output stage, we suggest a new approach that filters the data inputs, based on Technical Analysis (TA) signals. When the trading signals suggest that the conditions are positive (negative) for investments we use data from the previously documented positive (negative) periods in order to calculate the VaR. In this way, we use input data that are more representative of the financial conditions under examination and thus VaR estimations are more accurate and more representative (nonprocyclical) than the conventional models’ estimation that use the last nonfiltered [Formula: see text]-day observations. Testing our assumptions in the US stock market for the period 2000–2017, the empirical data confirmed our hypothesis. Moreover, we suggest specific legislative adjustments that contribute to more accurate and representative VaR estimations: (i) an extra backtesting procedure at a lower than the 99% confidence level as a procyclicality test and (ii) to ease the minimum requirement of 250 observations that is currently the input threshold because it leads to less accurate VaR estimations.
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Szczepanik, Jerzy, and Tomasz Sieńko. "Intuitive Multiphase Matrix Converter Control Procedures Applied to Power-System Phase Shifters." Energies 14, no. 15 (July 23, 2021): 4463. http://dx.doi.org/10.3390/en14154463.
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The article presents the concept of application of a multiphase matrix converter (MMC)-based device working as a phase-shifting control device in a power system. A matrix M × M multiphase converter is a simple structure incorporating M × M bidirectional switches, connecting M input phases to M output phases (a square structure is used). The device, in this research and under proposed control, is able to build M output sinusoidal-shape phases (desired output) from parts of input voltages. The proposed MMC-based device can be considered as a new flexible AC transmission system (FACTS) apparatus. Three basic control systems that enabled the creation of output waveforms as the combination of input ones were presented. Both 6 × 6 and 12 × 12 matrix structures were introduced, since 3 × 6 and 3 × 12 transformers are already in use. The mathematical, Simulink, and laboratory models were built to extract characteristic features of the MMC. The chosen “area-based” control procedure was based on finding a common point of area representing a certain switch (connecting a certain input and a certain output) and a time-dependent trajectory. Practical application of the MMC in a power system involves not only MMC analysis, but also the study of application requirements, possible converter topologies, and the development of new, reliable control algorithms. Particular consideration was given to the simplicity of the control and the analysis of the converter properties. The proposed control procedure did not use the PWM technique, but created output in similar way to a multilevel converter.
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Hosseinzadeh-Lotfi, Farhad, Gholam-Reza Jahanshahloo, and Mansour Mohammadpour. "An Extension of Cross Redundancy of Interval Scale Outputs and Inputs in DEA." Journal of Applied Mathematics 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/658635.
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It is well known that data envelopment analysis (DEA) models are sensitive to selection of input and output variables. As the number of variables increases, the ability to discriminate between the decision making units (DMUs) decreases. Thus, to preserve the discriminatory power of a DEA model, the number of inputs and outputs should be kept at a reasonable level. There are many cases in which an interval scale output in the sample is derived from the subtraction of nonnegative linear combination of ratio scale outputs and nonnegative linear combination of ratio scale inputs. There are also cases in which an interval scale input is derived from the subtraction of nonnegative linear combination of ratio scale inputs and nonnegative linear combination of ratio scale outputs. Lee and Choi (2010) called such interval scale output and input a cross redundancy. They proved that the addition or deletion of a cross-redundant output variable does not affect the efficiency estimates yielded by the CCR or BCC models. In this paper, we present an extension of cross redundancy of interval scale outputs and inputs in DEA models. We prove that the addition or deletion of a cross-redundant output and input variable does not affect the efficiency estimates yielded by the CCR or BCC models.
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Kulyk, М. M. "Modification of the Ghosh model structure in inter-sectoral analysis." Problems of General Energy 2020, no. 3 (September 24, 2020): 06–21. http://dx.doi.org/10.15407/pge2020.03.006.
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The current Ghosh model is based on the use of value-added forecast data. The forecasts of gross domestic product and value added have long and regularly been developed by different national and international economic and financial structures, including governmental ones. The level of methods and accuracy of such forecasts is quite high as compared with the final demand forecasts on which the Leontief model is based. Therefore, from the econometric point of view, the accuracy of predictions of output made by using the Ghosh model should be at least not worse than that provided by the classical Leontief model. The modified Ghosh model formally differs from its current model by the presence of a new matrix. However, this difference is only a structural feature, and in mathematical terms these models are identical. At the same time, the modified Ghosh model is more attractive and promising than the current one due to the following factors. It uses one matrix instead of two matrices that appear in the current model. The modified model has a structure (unlike the current one) similar to the structure of the classical Leontief model. Due to this, the modified model is more understandable and easy to use. However, the most important feature lies in the fact that the use of a new matrix significantly expands the possibilities of theoretical research within the input-output structures. Due to constructing a new matrix in the modified Ghosh model, new relations between the vectors of final demand and value added were discovered, which can be efficiently used in balancing the system of input-output matrices. It was also established that the corresponding matrices of the classical Leontief model and the modified Ghosh model have identical diagonal elements in pairs, and this is useful in various analytical studies. Keywords: modified Ghosh model, input-output, Leontief model, value added, final demand
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Burtnyak, Ivan, and Anna Malytska. "Modeling the Behavior of Banks in Instability Conditions." Journal of Vasyl Stefanyk Precarpathian National University 8, no. 3 (November 3, 2021): 35–42. http://dx.doi.org/10.15330/jpnu.8.3.35-42.
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The analysis of models of activity of banking structures in the conditions of perfect and imperfect competition is carried out. Production functions for financial companies are considered. Models of the bank's work as an institution of delegated monitoring are described. Models of dynamics of financial resources are analyzed, allow to describe processes of evolution of own capital of bank depending on dynamics of the involved resources and the policy of accumulation realized by it. The considered models and methods are based on the definition of a bank (a financial company) as some abstract object, which is characterized by input and output parameters, as well as the function that connects them. This approach to some extent allows adapting traditional models of research of industrial enterprises and organizations to the analysis of the activities of banking structures. Therefore, one of the main tasks is to optimize internal functioning. Under such conditions, it is especially important to consider the bank as a holistic complex dynamic system operating in an unstable transition economy and the use of economic and mathematical methods and models to study the processes taking place in the bank, assess its effectiveness, identify areas and ways to improve management banking activities. Based on the analysis of the main economic and mathematical models of behavior of financial companies in a monopolistic market, we can conclude that each model characterizes a certain aspect of financial market development by the situation. Production functions for a bank (financial firm) are built, where the problem of classification of these factors into input and output is significant. A wide class of economic and mathematical models is considered, in which the activity of financial and banking institutions is treated as financial intermediaries. The theory of delegated monitoring is generalized, which in the general case assumes that in conditions when there is an effect of the growth of income from scale, individual lenders prefer to delegate functions of control (monitoring) of the behavior of entrepreneurs in whose projects they have invested to special intermediary firms. banks. The analysis of the development of the banking sector of Ukraine showed that a further gradual slowdown in its pace is expected due to changes in conditions in global financial markets and market saturation.
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Golshan, Abolfazl, Soheil Gohari, and Ayob Amran. "Modeling and Optimization of Wire Electrical Discharge Machining of Cold-Work Steal 2601." Advanced Materials Research 383-390 (November 2011): 6695–703. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6695.
Full textAbstract:
In this study, the appropriate input parameters for achieving minimum surface roughness and high material removal rate are selected for wire electrical discharge machining of cold-work steel 2601. Mathematical modeling acquired by experimental result analysis is used to find the relation between input parameters including electrical current, gap voltage, open-circuit voltage and pulse-off time and output parameters. Subsequently, with exploitation of variance analysis, importance and effective percentages of each parameter are studied. The combination of optimum machining parameters is acquired using the analysis of ratios of signal-to-noise. Finally, according to multiple-objective optimization, outputs acquired from Non-dominated Sorting Genetic Algorithm led in achieving appropriate models. The optimization results showed suggested method has a high performance in problem solving.