Load sensor is developed using mamdani fuzzy inference system and sugeno fuzzy inference system. It is two input and one output sensor. Both mamdani-type fuzzy inference system and sugeno-type fuzzy inference system are simulated using MATLAB fuzzy logic toolbox. This paper outlines the basic difference between these two fuzzy inference system and their simulated results are compared. Index Ter...

image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

background : drivers are vulnerable to musculoskeletal and psychological disorders because of substantially harmful agents in this stressful occupation. this study aims to investigate the influence of driver’s physical and psychological health on the risk of road accidents using fuzzy logic approach. methods : two input variables including musculoskeletal disorders (msds) and mental health, alo...

Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decisionmaking model combining fuzzy log...

the late detection of the kick (the entrance of underground fluids into oil wells) leads to oil wellblowouts. it causes human life loss and imposes a great deal of expenses on the petroleum industry.this paper presents the application of adaptive neuro-fuzzy inference system designed for an earlierkick detection using measurable drilling parameters. in order to generate the initial fuzzy infere...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

This paper discusses design of adaptive Genetic Algorithms (GA) on the base Fuzzy Inference System (FIS). There are two possible ways for integrating Fuzzy Logic and Genetic Algorithms. One involves the applications of Genetic Algorithms for solving optimization and search problem related with fuzzy systems. The another, the use of “fuzzy tools” for modeling and adapting Genetic Algorithm contr...

Worms spread by scanning for vulnerable hosts across the Internet. In this paper we report a comparative study of three classification schemes for automated portscan detection. These schemes include a simple Fuzzy Inference System (FIS) that uses classical inductive learning, a Neural Network that uses back propagation algorithm and an Adaptive Neuro Fuzzy Inference System (ANFIS) that also emp...

The Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference System (FIS) has attracted a growing interest of researchers in various scientific and engineering areas due to the growing need for adaptive intelligent systems to solve real world problems. ANN learns by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory...

the present paper aimed at developing an approach based on fuzzy inference system (fis) for measuring of knowledge sharing in the organization. in recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find ...