scholarly journals THE USE OF FUZZY LOGIC WHILE MODELING THE CREDITWORTHINESS OF LEGAL ENTITIES

2020 ◽  
Vol 1 (2) ◽  
pp. 57-61
Author(s):  
Olga Palamarchuk
Keyword(s):  
Fuzzy Logic ◽  
Statistical Data ◽  
Expert Knowledge ◽  
Methodological Approach ◽  
Financial Statements ◽  
Rule Base ◽  
Decision Making Process ◽  
Domestic Enterprise ◽  
Practical Implications ◽  
Legal Entities

The purpose of the article is to develop a methodological approach to support the decision-making process in determining the creditworthiness of legal entities, as well as to create economic mathematical models based on this approach using the theory of fuzzy logic and fuzzy sets. Methodology. In the author's work (Palamarchuk, 2013), 49 real financial statements (Form 1 and Form 2) of Ukrainian enterprises were selected, 25 of which were potentially bankrupt and 24 were normally operating enterprises. As a result, 7 coefficients were obtained. Here we continue our modelling and building rule base. Result of the experiment is based on statistical data of domestic enterprise. The model has been constructed with the use of theory of fuzzy logic. Considering the expert knowledge, this model helps to make decisions on whether to provide the legal entity with the loan. Practical implications. The model and methodology can be used in commercial banks of Ukraine for calculating application risks. The known models do not fit to every economy. This is the reason which provides value originality of the topic of this study, which solves the problem of creating a method that would give the most sufficient assessment of creditworthiness.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

scholarly journals Assessment of the Performance Status of a Wharf

Pomorstvo ◽  
2018 ◽  
Vol 31 (1) ◽  
pp. 245-257
Author(s):  
Pereowei Garrick Ombor ◽  
Thaddeus C. Nwaoha
Keyword(s):  
Fuzzy Logic ◽  
Statistical Data ◽  
Performance Status ◽  
Rule Base ◽  
Subjective Judgement ◽  
The Status ◽  
Base Method ◽  
Logic Rule ◽  
Good Agreement

This paper suggests Fuzzy-logic-rule base method to assess the performance status of a wharf in order to classify it. The method proposed is predicated upon its ability to analyse processes and operations based on subjective judgement with little or no statistical data available. The study also shows that fuzzy-logic rule base is a veritable tool to qualitatively and quantitatively assess the status of a wharf offering ferry service. Using the model developed in this study, the performance status of Yenagoa wharf has been determined to be orange, having a (WPS) overall of 4.8. The status of the wharf has been in good agreement with the perception of stakeholders that the Yenagoa wharf needs restructuring to curb the frequent crisis occurring among stakeholders. The model also indicated those areas of the wharf’s operations needing attention. The study indicates that even though major components that determine the quality and profitability of the wharf’s ferry service are high in value, the overall status of the wharf may not be necessarily high. As such, the study method can be used to control the growing ill-feeling between boat operators and passengers while harmonizing all stakeholders (operators, passengers, and regulators etc) to work together to improve the status of the wharf.

A Method for Embedding Human Expert Knowledge Into a Fuzzy Logic Controller

1995 ◽  
Author(s):  
John R. Canning ◽  
Dean B. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Classification System ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Autonomous Vehicle ◽  
Sensor Data ◽  
Rule Base ◽  
Terrain Classification ◽  
Human Expert ◽  
Terrain Features

Abstract This paper presents a method for embedding human expert knowledge into a fuzzy logic controller. The method was developed while designing a fuzzy logic control system for an autonomous vehicle that utilized sparse sensor data for terrain classification. We will discuss the design for the fuzzy logic terrain classification system and use it as an example for explaining the embedding method. In the example, a human expert classified terrain features from sensor data provided by a two-dimensional computer simulation. From the information derived from the expert, we developed both a classification system for the terrain features and a fuzzy logic rule base for the controller. The simulation, along with an optimization algorithm, was then used to train the fuzzy logic controller to match the human responses.

How organizational constraints affect nurses’ decision in triage assessment performances

2018 ◽  
Vol 22 (4) ◽  
pp. 362-374 ◽  
Author(s):  
Lorella Cannavacciuolo ◽  
Adelaide Ippolito ◽  
Cristina Ponsiglione ◽  
Gaetano Rossi ◽  
Giuseppe Zollo
Keyword(s):  
Decision Making ◽  
Organizational Context ◽  
Methodological Approach ◽  
Organizational Factors ◽  
Public Hospitals ◽  
Decision Making Process ◽  
Content Type ◽  
Organizational Constraints ◽  
Decision Making Processes ◽  
Practical Implications

PurposeThis paper aims to investigate the performances of decision-making process of emergency department’s nurses involved in the triage level assessment.Design/methodology/approachThe authors developed a case study in two public hospitals in the South of Italy. The authors administered 25 clinical cases to nurses responsible of priority code assignment in the triage station. The authors simulated the attribution of the priority levels, and through a semi-structured questionnaire, the authors collected data and information about the cognitive process adopted for the final choice.FindingsThe quantitative and qualitative data allowed the authors to verify that there is an impact of the organizational context on heuristics used in the decision-making process.Research limitations/implicationsThe research limitations are that empirical data have been collected only in two emergency departments.Practical implicationsThe practical implications of this paper are that organizations for improving business performances must consider the judgements are often the results of heuristics embedded in a specific structure of social and physical environment, according with the “ecological view” of rationality.Originality/valueThe authors’ methodological approach contributes to analyze the performances of the triage process, verifying if the eventual errors are linked to individual or organizational factors, but above all how organizational constraints influence decision-making processes in organizations and, consequently, business performances.

Magnetic Bearing Control Using Interval Type-2 Fuzzy Logic

2005 ◽  
Author(s):  
Andra´s Simon ◽  
George T. Flowers
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Magnetic Bearing ◽  
Innovative Technology ◽  
Rule Base ◽  
Fuzzy Logic Systems ◽  
Limited Effectiveness ◽  
Logic Systems ◽  
Radial Magnetic Bearing

Magnetic bearings are an exciting and innovative technology that has seen considerable advances in recent years. Being unstable by nature, these systems require active control. Most often linear techniques are used very successfully. On the other hand, there are applications where linear methods have limited effectiveness. Fuzzy logic control performs very well in nonlinear control situations where the plant parameters are either partially or mostly unidentified. Its effectiveness for nonlinear systems also offers advantages to magnetic bearing systems. Type-2 fuzzy logic systems represent significant advances over traditional fuzzy logic systems in general. These fuzzy logic systems are capable to deal with uncertainties which can be found in almost every practical system. Uncertainties stem from several sources; noise present in the position input signals, the location and shape of fuzzy sets and the fuzzy rule-base describing the operation of the fuzzy controller, among others. Since a mathe-matical model of the controlled plant is often only a conveniently close approximation of the real process at hand, a major challenge lies in the application of the control methods to real plants. Type-2 fuzzy logic and fuzzy logic systems in general tackle the control problem at hand using human reasoning based on rules and expert knowledge of the plant described by human expressions. The current work consist of model development, controller design, simulation and experimental validation. The basic simulation model consist of a horizontal shaft supported by a radial magnetic bearing. The magnetic bearing is modeled as a nonlinear element. The controller designs are implemented and tested using a bench-top rotor rig equipped with a radial magnetic bearing. Some representative results are presented and discussed.

scholarly journals Assessment of the Performance Status of a Wharf

Pomorstvo ◽  
2018 ◽  
Vol 32 (2) ◽  
pp. 245-257
Author(s):  
Pereowei Garrick Ombor ◽  
Thaddeus C. Nwaoha
Keyword(s):  
Fuzzy Logic ◽  
Statistical Data ◽  
Performance Status ◽  
Rule Base ◽  
Subjective Judgement ◽  
The Status ◽  
Base Method ◽  
Logic Rule ◽  
Good Agreement

This paper suggests Fuzzy-logic-rule base method to assess the performance status of a wharf in order to classify it. The method proposed is predicated upon its ability to analyse processes and operations based on subjective judgement with little or no statistical data available. The study also shows that fuzzy-logic rule base is a veritable tool to qualitatively and quantitatively assess the status of a wharf offering ferry service. Using the model developed in this study, the performance status of Yenagoa wharf has been determined to be orange, having a (WPS) overall of 4.8. The status of the wharf has been in good agreement with the perception of stakeholders that the Yenagoa wharf needs restructuring to curb the frequent crisis occurring among stakeholders. The model also indicated those areas of the wharf’s operations needing attention. The study indicates that even though major components that determine the quality and profitability of the wharf’s ferry service are high in value, the overall status of the wharf may not be necessarily high. As such, the study method can be used to control the growing ill-feeling between boat operators and passengers while harmonizing all stakeholders (operators, passengers, and regulators etc) to work together to improve the status of the wharf.

scholarly journals TRENDS OF MUNICIPAL WASTE FLOWS, COMPOSITION, TREATMENT IN LITHUANIA AND ITS REGIONS

2021 ◽  
Author(s):  
Jelena Stankevičienė ◽  
Julija Bužinskė
Keyword(s):  
Conceptual Model ◽  
Statistical Data ◽  
Scientific Literature ◽  
Local Level ◽  
Regional Level ◽  
Municipal Waste ◽  
Decision Making Process ◽  
Active Involvement ◽  
Its Regions ◽  
Practical Implications

Purpose – to propose conceptual model for forecasting of waste trends and empirically implement the model based on the case of Lithuania and its regions. Research methodology – 1) scientific literature analysis on circular economy, zero waste and waste management, 2) gathering of statistical data on waste flows, composition and treatment 3) creation of conceptual model of forecasting with Exponential Smoothing for prediction of waste-related trends based on literature review. Findings – proposed conceptual model for prediction of waste-related trends is adequate for prognosis of waste flows, composition and treatment ways. The main forecasting results are that the total waste flows will increase in Lithuania, on a regional level, Alytus, Kaunas, Klaipėda, Telšiai, have a tendency of the increase in municipal waste flows. The results imply that in order to contribute to the reduction of waste, the active involvement on a regional level is necessary. Research limitations – the research can be extended with statistical data on waste of other countries to check adequacy of the conceptual model for waste-related trends prognosis. Practical implications – the findings of the research can be applied in planning and decision-making process of gov-ernment bodies on national or local level. The results are also useful for the general public in educational purposes. Originality/Value – the study provides original conceptual model for the forecasting of waste-related trends which provides robust results of predictions and can be replicated by different countries.

SCORING MODELING BASED ON NEURAL NETWORKS FOR DETERMINING A BANK BORROWER'S RATING

2020 ◽  
Vol 2020 (10) ◽  
pp. 54-62
Author(s):  
Oleksii VASYLIEV ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Statistical Data ◽  
Activation Function ◽  
Decision Making Process ◽  
Neural Network Architecture ◽  
Acceptable Accuracy ◽  
The Neural Network ◽  
Sigmoid Activation Function

The problem of applying neural networks to calculate ratings used in banking in the decision-making process on granting or not granting loans to borrowers is considered. The task is to determine the rating function of the borrower based on a set of statistical data on the effectiveness of loans provided by the bank. When constructing a regression model to calculate the rating function, it is necessary to know its general form. If so, the task is to calculate the parameters that are included in the expression for the rating function. In contrast to this approach, in the case of using neural networks, there is no need to specify the general form for the rating function. Instead, certain neural network architecture is chosen and parameters are calculated for it on the basis of statistical data. Importantly, the same neural network architecture can be used to process different sets of statistical data. The disadvantages of using neural networks include the need to calculate a large number of parameters. There is also no universal algorithm that would determine the optimal neural network architecture. As an example of the use of neural networks to determine the borrower's rating, a model system is considered, in which the borrower's rating is determined by a known non-analytical rating function. A neural network with two inner layers, which contain, respectively, three and two neurons and have a sigmoid activation function, is used for modeling. It is shown that the use of the neural network allows restoring the borrower's rating function with quite acceptable accuracy.

Regularities of development small entrepreneurship in regions 2015-2018

2019 ◽  
Vol 39 (2) ◽  
pp. 73-80
Author(s):  
I. S. Pinkovetskaia
Keyword(s):  
Initial Data ◽  
Statistical Data ◽  
Russian Economy ◽  
Business Structures ◽  
Regions Of Russia ◽  
Legal Entities

The aim of the study, the results of which are given in this paper, was to assess the saturation of the Russian economy with business structures. Statistical data for 2015 and 2017 were used as initial data. The indicators characterizing activity of subjects small entrepreneurship (legal entities and individual entrepreneurs) in regions of Russia are presented.

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

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