File Name: fuzzy sets decision making and expert systems writer.zip
- Fuzzy Logic and Neural Networks Based Expert Systems in Chemical Process Systems
- Fuzzy logic
- A Novel Fuzzy Expert System for the Identification of Severity of Carpal Tunnel Syndrome
Fuzzy Logic and Neural Networks Based Expert Systems in Chemical Process Systems
Fuzzy Logic Systems FLS produce acceptable but definite output in response to incomplete, ambiguous, distorted, or inaccurate fuzzy input. Fuzzy Logic FL is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO. It can be implemented in systems with various sizes and capabilities ranging from small micro-controllers to large, networked, workstation-based control systems. Membership functions allow you to quantify linguistic term and represent a fuzzy set graphically.
Citation: Jayalakshmi M, Vijayaraghavan G. Int J Chem Sci. Recently planning and functioning of a Chemical Process Systems CPS has become more essential and many sophisticated tools were used. In this article, the application of fuzzy logic and neural network based expert systems in CPS was discussed. A brief discussion on fuzzy set theory and its characteristics were presented. Also, the importance of knowledge based expert system on CPS to attain extreme production and high safety was sketched. It was observed that there are several expert systems biased only on fuzzy logic and neural networks; hence it is recommended that the fuzzy logic and neural networks based expert systems in chemical process systems will be an efficient one.
In fuzzy mathematics , fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1 both inclusive. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false. The term fuzzy logic was introduced with the proposal of fuzzy set theory by Lotfi Zadeh. Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or sets are mathematical means of representing vagueness and imprecise information hence the term fuzzy. These models have the capability of recognising, representing, manipulating, interpreting, and utilising data and information that are vague and lack certainty. Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.
Thus, fuzzy expert systems are increasingly being used to solve decision-making problems by attempting to solve a part or whole of a practical problem. These expert systems have proven that they can solve problems in various domains where human expertise is required, including the field of agriculture. Fuzzy Expert Systems and Applications in Agricultural Diagnosis is a crucial source that examines the use of fuzzy expert systems for prediction and problem solving in the agricultural industry. Featuring research on topics such as nutrition management, sustainable agriculture, and defuzzification, this book is ideally designed for farmers, researchers, scientists, academics, students, policymakers, and development practitioners seeking the latest research in technological tools that support crop disease diagnosis. Buy Hardcover. Add to Cart. More Information.
The diagnosis of carpal tunnel syndrome, a peripheral nerve disorder, at the earliest possible stage is very crucial because if left untreated it may cause permanent nerve damage reducing the chances of successful treatment. The data used were the nerve conduction study data obtained from Kannur Medical College, India. It consists of thirteen input fields, which include the clinical values of the diagnostic test and the clinical symptoms, and the output field gives the disease severity. Since quantification of the intensity of CTS is a crucial step in the electrodiagnostic procedure and is important for defining prognosis and therapeutic measures, such an expert system can be of immense use in those regions where the service of such specialists may not be readily available. It may also prove useful in combination with other systems in providing diagnostic and predictive medical opinions and can add value if introduced into the routine clinical consultations to arrive at the most accurate medical diagnosis in a timely manner.
Since its launching in , the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including and not restricted to aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis.
PDF | Expert System (ES) is considered to be the prominent reasoning practices This editor maintains high-level problems in a framework that includes a fuzzy logic and expert system for decision-making of services centre management.
A Novel Fuzzy Expert System for the Identification of Severity of Carpal Tunnel Syndrome
Lung cancer is the most common type of cancer around the world, and it represents the main cause of death in the USA. Surgical treatment is the optimal therapeutic strategy for resectable non-small cell lung cancer. The principal factor for long-term survival after complete resection is the anatomic extension of the neoplasm. However, other factors also have adverse effects on operative mortality, and influence long-term outcome. In this paper we propose an algorithmic solution for the estimation of 5-years survival rate in lung cancer patients undertaking pulmonary resection.
Herrera , S. Alonso , F. Chiclana , E. Fuzzy Optimization and Decision Making, , doi:
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