scholarly journals Fuzzy model of the computer integrated decision support and management system in mineral processing

2008 ◽  
Vol 18 (2) ◽  
pp. 253-259 ◽  
Author(s):  
Igor Miljanovic ◽  
Slobodan Vujic

During the research on the subject of computer integrated systems for decision making and management support in mineral processing based on fuzzy logic, realized at the Department of Applied Computing and System Engineering of the Faculty of Mining and Geology, University of Belgrade, for the needs of doctoral thesis of the first author, and wider demands of the mineral industry, the incompleteness of the developed and contemporary computer integrated systems fuzzy models was noticed. The paper presents an original model with the seven staged hierarchical monitoring-management structure, in which the shortcomings of the models utilized today were eliminated.

Author(s):  
V. B. Kropyvnytska ◽  
O. V. Yefremov ◽  
H. N. Sementsov

The article deals with the issue of Fuzzy-simulation of controllers for solving practical problems of automated control. The peculiarities of Fuzzy-simulation of cascade controllers in the Matlab environment are studied. The presentation is accompanied by examples of the development of individual Fuzzy models and an illustration of conducting all necessary operations with fuzzy sets.


Kybernetes ◽  
2018 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luciano Barcellos de Paula ◽  
Anna Maria Gil-Lafuente

PurposeScientific studies indicate that stakeholder’s engagement is a key factor for the creation of sustainable value in companies. This paper aims to evaluate the sustainability of a sports company and propose a tool to prioritize the relevant issues that this company should consider in its operations.Design/methodology/approachStakeholder theory and Global Reporting Initiative (GRI) are considered, and, from the Fuzzy Logic, the paper proposes a decision-making tool to establish the relevant issues. The “Experton Method” is used in this paper.FindingsThe algorithm used can help decision makers in processes that include the stakeholder’s opinions. In this case, a tool that treats qualitative data in a reliable manner is required. The methodology used allowed knowing the stakeholders expectations and to define priorities in sustainability issues. The results were captured in a materiality matrix. The manuscript concludes that including stakeholders in the decision-making process, the company generates trust and legitimacy of its stakeholders. This participatory approach and the use of algorithm help companies in materiality assessment, definition of priority issues and management of resources.Practical implicationsIn terms of managerial implications, this paper presents a useful tool that can help entrepreneurs in the decision-making to manage their suppliers. Using an algorithm of fuzzy logic applied in the supply chain management, it is indicated how to set priorities to build a consistent corporate social responsibility (CSR) plan to achieve corporation success. This methodology allows reducing subjectivity; it generates greater precision and decreases the risk in decision-making. At the same time, it promotes dialogue and collaboration among stakeholders to create value for stakeholders and CSR, and collaborate to have a responsible company performance. Furthermore, this paper provides theoretical applications in terms of the literature review on corporate sustainability, indicating that companies must consider the stakeholder’s engagement in its strategies. Based on the bibliometric study, there are knowledge gaps on the subject. For these reasons, an important contribution is observed at the academic level that allows expanding the frontier of knowledge on the subject.Originality/valueA tool for decision-making is presented with great utility for entrepreneurs in the processes of dialogue and stakeholder’s engagement, being a contribution for the creation of sustainable value. In addition, there is an important scientific contribution because the paper identifies in the literature the knowledge gaps on the subject.


Author(s):  
Alexandre Vieira de Oliveira ◽  
David Barbosa de Alencar ◽  
Alexandra Priscilla Tregue Costa ◽  
Manoel Henrique Reis Nascimento

This paper introduces the concept of fuzzy logic, some terms used in this kind of logic, and uses it to evaluate and choose where to deploy factories and other enterprises. In addition, a model is made using the InFuzzy program to evaluate a choice of a location within the Manaus Industrial Pole - PIM, using objective and subjective criteria within the fuzzy logic. This article aims to present the fuzzy logic in the context of production engineering, select the parameters that define the best location, develop models that represent the subject in the study and verify the applicability by simulating other case studies and comparing results.


Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 126 ◽  
Author(s):  
Vlasenko ◽  
Vlasenko ◽  
Vynokurova ◽  
Bodyanskiy ◽  
Peleshko

Neuro-fuzzy models have a proven record of successful application in finance. Forecasting future values is a crucial element of successful decision making in trading. In this paper, a novel ensemble neuro-fuzzy model is proposed to overcome limitations and improve the previously successfully applied a five-layer multidimensional Gaussian neuro-fuzzy model and its learning. The proposed solution allows skipping the error-prone hyperparameters selection process and shows better accuracy results in real life financial data.


2010 ◽  
Vol 2010 ◽  
pp. 1-29 ◽  
Author(s):  
Sehraneh Ghaemi ◽  
Sohrab Khanmohammadi ◽  
Mohammadali Tinati

In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model calledModel Iis presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules calledModel IIandModel IIIby using Sugeno fuzzy inference.Model IIandModel IIIhave less linguistic terms thanModel Ifor the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.


2015 ◽  
Vol 17 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Radek Doskočil

The article deals with the use of fuzzy logic as a support of evaluation of total project risk. A brief description of actual project risk management, fuzzy set theory, fuzzy logic and the process of calculation is given. The major goal of this paper is to present am new expert decision-making fuzzy model for evaluating total project risk. This fuzzy model based on RIPRAN method. RIPRAN (RIsk PRoject ANalysis) method is an empirical method for the analysis of project risks. The Fuzzy Logic Toolbox in MATLAB software was used to create the decision-making fuzzy model. The advantage of the fuzzy model is the ability to transform the input variables The Number of Sub-Risks (NSR) and The Total Value of Sub-Risks (TVSR) to linguistic variables, as well as linguistic evaluation of the Total Value of Project Risk (TVPR) – output variable. With this approach it is possible to simulate the risk value and uncertainty that are always associated with real projects. The scheme of the model, rule block, attributes and their membership functions are mentioned in a case study. The use of fuzzy logic is a particular advantage in decision-making processes where description by algorithms is extremely difficult and criteria are multiplied.


2019 ◽  
Vol 15 (1) ◽  
pp. 51-83 ◽  
Author(s):  
Raghda Hraiz ◽  
Mariam Khader ◽  
Adnan Shaout

Assessing applicants for faculty positions in universities involves many issues. Each issue may involve a judgment based on uncertain or imprecise data. The uncertainty in data may exist in the interpretation made by the evaluator. This issue might lead to improper decision making. Modeling such a system using fuzzy logic will provide a more efficient model for handling imprecision. This article presents a fuzzy system for modeling the assessment of applicants for employment at academic universities. This system will utilize a multi-stage fuzzy model for measuring and evaluating the applicants. Utilizing fuzzy logic for applicants' evaluation will help administrators in choosing the best candidates for faculty positions. The fuzzy system was developed using jFuzzyLogic Java library. The reliability of the proposed system was proved by evaluating real-world case studies to prove its effectiveness to mimic human judgment. Moreover, the developed system has been evaluated by comparing it with a traditional mathematical method to prove the credibility and fairness of the proposed fuzzy system.


Author(s):  
Tatiana Sergeevna Stankevich

The article studies the problem of control of firefighting at the seaports under uncertainty, which consists of localization and extinguishing fire with minimum effort and resources within shortest time. The author has developed a model of fire fighting control at the seaports under conditions of uncertainty, the main elements of which are: a model of defining the fire area; a model of selecting the fire rank; an analytical model for evaluating resources sufficiency; an analytical model for resources selection; a neuro-fuzzy model for choosing optimal actions; an evaluation model of successful implementation of the plan; a model for implementation of neuro-fuzzy models. In comparison with existing models, distinctive features of the developed model are the following: application of combined membership functions that allow to perform more accurate approximation of input parameters values; implementation of the block of eliminating dynamic errors. This article assesses the model adequacy and confirms it through model verification and validation. The author has developed information and analytical management support system for fire fighting at seaports which can be used by the chief fire-fighters under uncertainty and is based on the developed model. The developed software is designed to raise the firefighters’ efficiency due to the increase of accuracy of managerial decisions taken by the chief firefighters and reduction of time necessary for decision making.


2011 ◽  
Vol 6 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Luis G. Martínez ◽  
Juan R. Castro ◽  
Antonio Rodríguez-Díaz ◽  
Guillermo Licea

Author(s):  
Krzysztof Zatwarnicki

Adaptive control of cluster-based Web systems using neuro-fuzzy modelsA significant development of Web technologies requires the application of more and more complex systems and algorithms for maintaining high quality of Web services. Presently, not only simple decision-making tools but also complex adaptation algorithms using artificial intelligence techniques are applied for controlling HTTP request traffic. The paper presents a new LFNRD (Local Fuzzy-Neural Adaptive Request Distribution) algorithm for request distribution in cluster-based Web systems using neuro-fuzzy models of Web servers in the decision-making process. The neuro-fuzzy model which is applied is discussed in detail and a design of the Web switch using the proposed solution is presented. Finally, a testbed is described and the results of a comparative simulation study on the LFNRD algorithm, and other algorithms known from the literature and used in the industry, are presented and discussed.


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