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Author(s):  
Javier Eduardo Martinez Baquero ◽  
Jairo Cuero Ortega ◽  
Robinson Jimenez Moreno

This article presents the design of a fuzzy controller embedded in a microcontroller aimed at implementing a low-cost, modular process control system. The fuzzy system's construction is based on a classical proportional and derivative controller, where inputs of error and its derivate depend on the difference between the desired setpoint and the actual level; the goal is to control the water level of coupled tanks. The process is oriented to control based on the knowledge that facilitates the adjustment of the output variable without complex mathematical modeling. In different response tests of the fuzzy controller, a maximum over-impulse greater than 8% or a steady-state error greater than 2.1% was not evidenced when varying the setpoint.


Author(s):  
Renata G. de Oliveira Fontan ◽  
Rodrigo Alvarenga Rosa ◽  
Adonai José Lacruz

ABSTRACT Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.


Author(s):  
Renata G. de Oliveira Fontan ◽  
Rodrigo Alvarenga Rosa ◽  
Adonai José Lacruz

ABSTRACT Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Chao Yang ◽  
Feng He ◽  
Chang Ren

Economic development in China requires lots of energy to support it, but how to acquire an adequate energy supply is a difficult problem. Meantime, environmental pollution caused by energy consumption is a problem that immediately needs to be solved. To adapt to China’s rapidly emerging economy, and based on existing policies, giving more consideration to energy saving and environmental safety is more important. Therefore, to investigate China’s regional environmental efficiency and its factors has key importance. In order to evaluate the environmental efficiency input in China, this study first selects some indexes of environmental efficiency and applies the Data Envelopment Analysis (DAE) method to measure the efficiency of input and output. Then, the relative index of environmental efficiency input is selected as the input variable and the efficiency value as the output variable. The Backpropagation neural network is employed to learn and establish the prediction model and achieve high prediction accuracy. The performance of the model is improved by optimizing the index of environmental efficiency investment, adopting the latest data, and increasing the learning samples. This method is not only suitable for the evaluation of macro-environmental efficiency investment, but also suitable for enterprises in specific industries.


2021 ◽  
Vol 89 (3) ◽  
Author(s):  
Sridhar Chellappa ◽  
Lihong Feng ◽  
Peter Benner

AbstractWe present a subsampling strategy for the offline stage of the Reduced Basis Method. The approach is aimed at bringing down the considerable offline costs associated with using a finely-sampled training set. The proposed algorithm exploits the potential of the pivoted QR decomposition and the discrete empirical interpolation method to identify important parameter samples. It consists of two stages. In the first stage, we construct a low-fidelity approximation to the solution manifold over a fine training set. Then, for the available low-fidelity snapshots of the output variable, we apply the pivoted QR decomposition or the discrete empirical interpolation method to identify a set of sparse sampling locations in the parameter domain. These points reveal the structure of the parametric dependence of the output variable. The second stage proceeds with a subsampled training set containing a by far smaller number of parameters than the initial training set. Different subsampling strategies inspired from recent variants of the empirical interpolation method are also considered. Tests on benchmark examples justify the new approach and show its potential to substantially speed up the offline stage of the Reduced Basis Method, while generating reliable reduced-order models.


2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Tengfei Jiang ◽  
Annan Jiang ◽  
Shuai Zheng ◽  
Mengfei Xu

Rock blasting often has an irreversible impact on the surrounding environment and threatens the safety of life and property. Therefore, accurate prediction of blast-induced ground vibration (BIGV) is a prerequisite for safe construction. In view of the fact that traditional blasting peak particle velocity (PPV) empirical formulas cannot be accurately predicted, this study selected 88 sets of blasting monitoring data, based on distance from the blast-face, maximum charge per delay, total charge, hole depth, spacing, burden, stemming length, and powder factor being used as input variables and PPV being used as output variable to characterize BIGV. First, a nonlinear mapping relationship between input variables and output variable is established through the Gaussian process (GP). The differential evolution algorithm (DE) is used to optimize the hyperparameters σf, σn, and l of the GP, and a blasting PPV model based on the DE-GP is constructed. The proposed model is compared with the empirical formulas, least square support vector machine (LSSVM), artificial neural network (ANN), and GP model, and its prediction performance is evaluated by statistical indicators such as root mean square error (RMSE). Finally, the cosine amplitude method (CAM) is used to analyze the sensitivity of blasting parameters. The results show that the DE-GP algorithm for blasting vibration velocity prediction has higher precision and accuracy, which is significantly better than other models, and is the closest to the measured PPV. Distance from the blast-face, total charge, and maximum charge per delay have a greater impact on the prediction of PPV, while stemming length and powder factor have a smaller impact on the prediction of PPV. The DE-GP model proposed by this research has certain reference value for the prediction and control of PPV in blasting construction.


Author(s):  
Juliana Câmara de Souza ◽  
Manoel Henrique Reis Nascimento

The contemporary business environment seeks continuous improvement to remain competitive in the market, as customers increasingly demand quality products or services. In this perspective, this paper presents a methodology aimed at evaluating the quality of processes in the project management sector in a Third Sector Organization, based on the Fuzzy mathematical model. For this, linguistic variables (input) were developed according to information obtained from company Y, which enabled the application of the Fuzzy Logic method, in order to determine the output variable, which in this case is quality. After determining the rules, it was possible to obtain results that show that the developed fuzzy model has the potential to help improve the quality of processes.


2021 ◽  
pp. 433-439
Author(s):  
Ekaterina Gribanova

This paper is devoted to solving inverse problems of simulation modeling, which are presented in the form of an optimization problem. The article discusses the use of direct search methods taking into account the specifics of the problem under consideration. Due to the fact that these methods require a lot of computational experiments, two algorithms based on approximation were proposed for solving the problem. The first algorithm consists in determining and evaluating the parameters of the function of dependence (which can be linear or non-linear) of the output variable on the input variables and solving the inverse problem by minimizing increments of the arguments. In the second algorithm a linear function of dependence is iteratively constructed using the data set generated by changing the input variables in given increments, and the inverse problem is solved by minimizing increments of the arguments. The classical inventory management model with a threshold strategy is considered as an example. The inverse problem was solved using direct search and approximation-based methods.


2021 ◽  
Vol 7 (4) ◽  
pp. 123-135
Author(s):  
Valentin Myachin ◽  
Olena Yudina ◽  
Oleksandr Myroshnychenko

The purpose of this study is to build a fuzzy expert system for assessing the financial component of the economic security of telecommunications enterprises. The methodological basis of the research is founded on scientific works of domestic and foreign scientists and leading experts in the field of financial analysis and modeling of economic processes, as well as statistical and financial reporting data that are publicly available. To construct an integral indicator of the financial security of an enterprise, a fuzzy conclusion is used. Three financial indicators are used as input variables. The first indicator X1 is the Current Ratio (CR). The second indicator X2 is Equity Ratio (ER). The third indicator is Return on Assets (ROA). The output variable is defined as an indicator of the financial security of an enterprise Y123 (FS). Both the input variables and the output variable are converted to fuzziness by constructing membership functions. The type and parameters of the affiliation function are justified, and the bell-shaped affiliation function is chosen to describe the uncertainty of values that fall under the normal distribution. The quantity of fuzzy sets at every input is considered as z=3 and the quantity of input variables is considered as ω=3. To achieve completeness of the model, the quantity of logic rules is considered as r=33=9. To calculate a degree of market concentration, Mamdani fuzzy conclusion is applied. Defuzzification is engaged to calculate the value of the output variable Y123(FS) for an indicator that determines the degree of financial security of an enterprise and, as a result, the degree of its economic security. To assess the level of the financial security indicator of an enterprise, a fuzzy expert system is constructed. The fuzzy expert system allows you to use various indicators thanks to the fuzzy logic methodology, which takes into account the fuzziness of input variables and output variables as much as possible. For the three telecommunications companies whose core business is wireline communication, ratios are calculated based on financial reports. Financial coefficients are used to determine the integral indicator of financial security of enterprises. This indicator can be characterized by both numerical values and linguistic terms.


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