Type-2 fuzzy sets and their variants
Ini John Umoeka; Veronica Neekay Akwukwuma
Abstract
The reliability of software product is seen as critical quality factor that cannot be overemphasized. Since real world application is loaded with high amount of uncertainty, such as applicable to software reliability, there should be a technique of dealing with such uncertainty. This paper presents a ...
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The reliability of software product is seen as critical quality factor that cannot be overemphasized. Since real world application is loaded with high amount of uncertainty, such as applicable to software reliability, there should be a technique of dealing with such uncertainty. This paper presents a reliability model to effectively handle uncertainty in software data to enhance reliability prediction of software at the early (requirements and design) stages of Software Development Life Cycle (SDLC). In this paper, a hybrid methodology of Takagi Sugeno Kang (TSK)-based Interval Type-2 Fuzzy Logic System (IT2FLS) with Artificial Neural Network (ANN) learning is employed for the prediction of software reliability. The parameters of the model are optimized using Gradient Descent (GD) back-propagation method. Relevant reliability software requirement and design metrics and software size metrics are utilized as inputs. The proposed approach uses twenty-eight real software project data. The performance of the model is evaluated using five performance metrics and found to provide output values that are very close to the actual output showing better predictive accuracy.
Fuzzy sets and their variants
Shaveta Arora; Renu Vadhera; Bharti Chugh
Abstract
COVID-19, an epidemic disease, has challenged human lives all over the world. Governments and scientific communities are trying their level best to help the masses. This disease which is caused by corona virus majorly attacks the upper respiratory system rendering the human immunity incapacitated and, ...
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COVID-19, an epidemic disease, has challenged human lives all over the world. Governments and scientific communities are trying their level best to help the masses. This disease which is caused by corona virus majorly attacks the upper respiratory system rendering the human immunity incapacitated and, in some cases, proving fatal. Therefore, it is very much important to identify the infected people quickly and accurately, so that it can be prevented from spread. Early addressal of the symptoms can help to prevent the disease to become severe for all mankind. This calls for the development of a decision-making system to help the medical fraternity for the timely action. This proposed fuzzy based system predicts Covid-19 based on individuals’ symptoms and parameters. It receives input parameters as fever, cough, breathing difficulty, muscle ache, sore throat, travel history, age, medical history in the form of different membership functions and generates one output that predicts the likelihood of a person being infected with COVID-19 using Mamdani fuzzy inference system. The timely prognosis of the disease at home isolation or at the security checks can help the patient to seek the medical treatment as early as possible. Patient case studies, real time observations, cluster cases were studied to create the rule base for FDMS. The results are validated by using real-time individuals test cases on the proposed system which yields 97.2% accuracy, 100% sensitivity and 96.2% specificity.
Fuzzy sets and their variants
Semiu Ayinla Alayande; Ezekiel Akande; Amanze Egere
Abstract
The purpose of this paper is to describe and present applications of fuzzy logic in analysis of certain neuro-psychopathological symptoms. These symptoms have been linked to conditions relating to occupational hazards. Our method of data analysis which is based on Hamacher operation on picture fuzzy ...
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The purpose of this paper is to describe and present applications of fuzzy logic in analysis of certain neuro-psychopathological symptoms. These symptoms have been linked to conditions relating to occupational hazards. Our method of data analysis which is based on Hamacher operation on picture fuzzy sets is then applied to analyze such occupational hazards. Our result proves to be effective and applicable in medical decision processes especially in situations where such neuro-psychopathological symptoms are detectable by first-aid diagnostic machines.
Fuzzy sets and their variants
Meysam Kaviani; Seyed Fakhreddin Fakhrehosseini
Abstract
Over the past decades, financial researchers have proposed different methods in portfolio selection, so that, Markwotiz [1] introduced risk and return criteria for a portfolio selection. Since it is difficult how to select an adequate stock portfolio, fuzzy models have been able to help researchers by ...
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Over the past decades, financial researchers have proposed different methods in portfolio selection, so that, Markwotiz [1] introduced risk and return criteria for a portfolio selection. Since it is difficult how to select an adequate stock portfolio, fuzzy models have been able to help researchers by considering uncertainty. In this research, we surveyed a portfolio management by reviewing the relevant literature of fuzzy model in financial management. The results showed that a fuzzy model can to determine an optimal portfolio.
Fuzzy sets and their variants
Mohsen Imeni
Abstract
Many areas of accounting have highly ambiguous due to undefined and inaccurate terms. Many ambiguities are generated by the human mind. In the field of accounting, these ambiguities lead to the creation of uncertain information. Many of the targets and concepts of accounting with binary classification ...
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Many areas of accounting have highly ambiguous due to undefined and inaccurate terms. Many ambiguities are generated by the human mind. In the field of accounting, these ambiguities lead to the creation of uncertain information. Many of the targets and concepts of accounting with binary classification are not consistent. Similarly, the discussion of the materiality or reliability of accounting is not a two-part concept. Because there are degrees of materiality or reliability. Therefore, these ambiguities lead to the presentation information that is not suitable for decision making. Lack of attention to the issue of ambiguity in management accounting techniques, auditing procedures, and financial reporting may lead to a reduced role of accounting information in decision-making processes. Because information plays an important role in economic decision-making, and no doubt, the quality of their, including accuracy in providing it to a wide range of users, can be useful for decision-making. One of the features of the fuzzy set is that it reduces the need for accurate data in decision making. Hence this information can be useful for users.
