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- Artificial Intelligence - Fuzzy Logic Systems
- Fuzzy logic
- A Novel Fuzzy Expert System for the Identification of Severity of Carpal Tunnel Syndrome
- Guide for Authors

The italicized words are the sources of fuzziness in these examples. Fuzzy goals and fuzzy constraints can be defined precisely as fuzzy sets in the space of alternatives. A fuzzy decision, then, may be viewed as an intersection of the given goals and constraints. A maximizing decision is defined as a point in the space of alternatives at which the membership function of a fuzzy decision attains its maximum value. The use of these concepts is illustrated by examples involving multistage decision processes in which the system under control is either deterministic or stochastic.

## Artificial Intelligence - Fuzzy Logic Systems

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. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods.

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.

Herrera , S. Alonso , F. Chiclana , E. Fuzzy Optimization and Decision Making, , doi: Ruan, F. International Journal of Computational Intelligence Systems, ,

## Fuzzy logic

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.

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. We address the issue of survival analysis through decision-making techniques based on fuzzy and soft set theories. We develop an expert system based on clinical and functional data of lung cancer resections in patients with cancer that can be used to predict the survival of patients.

The main goal of this paper is to develop an expert system based on fuzzy set theory that will provide more successful and efficient decision making in the area.

## A Novel Fuzzy Expert System for the Identification of Severity of Carpal Tunnel Syndrome

During the last three decades, the potential of electronic data processing EDP has been used to an increasing degree to support human decision making in different ways. In the sixties the management informations systems MIS created probably exaggerated hopes of managers. Since the late s and early s decision support systems DSS found their way into management and engineering. The youngest children of these developments are the so-called knowledge-based expert systems or short expert systems which have been applied since the mid s to solve management problems [Zimmermann , p. It is generally assumed that expert systems will increasingly influence decision-making processes in business in the future.

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.

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.

### Guide for Authors

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expert systems, one uses fuzzy logic toolbox graphical user interface (GUI) tools to build up a fuzzy inference system (FIS) to aid in decision-making. FIGURE THE MEMBERSHIP FUNCTION EDITOR PRESENTING INPUT 1, WHICH.

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assumed that expert systems will increasingly inftuence decision-making processes in apparent there; and hence the application of fuzzy set theory is most promising and knowledge elicitation could consist of a user-friendly rule editor, an.

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Citation: Jayalakshmi M, Vijayaraghavan G.