نتایج جستجو برای: fuzzy inference system fis

تعداد نتایج: 2363962  

The paper deals with devising the combination of fuzzy inference systems (FIS) and neural networks called the adaptive network fuzzy inference system (ANFIS) to determine the forming limit diagram (FLD). In this paper, FLDs are determined experimentally for two grades of low carbon steel sheets using out-of-plane (dome) formability test. The effect of different parameters such as work hardening...

2009
Liliana D'Errico Michele Loreti

Fuzzy systems address the imprecision of the input and output variables, which formally describe notions like “rather warm” or “pretty cold”, while provide a behaviour that depends on fuzzy data. This class of systems are classically represented by means of Fuzzy Inference Systems (FIS), a computing framework based on the concepts of fuzzy if-then rules and fuzzy reasoning. Even if FIS are larg...

2012
Hamid Reza Rezaei

The key issue of inventory management is the problem of safety stock control. The existence of imprecise data makes this control complex. Fuzzy logic (FL) is widely used to develop expert system, due to its ability in representing imprecise data. Therefore, in this study a fuzzy logic system and theory have been used that incorporate the linguistic variable more practically and also help in eli...

2011
Hossein Abbasimehr Mostafa Setak M. J. Tarokh

Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...

2016
Deepak Kumar Verma H. S. Shukla

Artificial intelligence techniques are day by day getting involvement in all the classification and prediction based process like environmental monitoring, stock exchange conditions, biomedical diagnosis, software engineering etc. However still there are yet to be simplify the challenges of selecting training criteria for design of artificial intelligence models used for prediction of results. ...

Journal: :Research in Computing Science 2017
Federico Furlán Colón Elsa Rubio-Espino Juan Humberto Sossa Azuela Víctor Hugo Ponce Ponce

This paper presents a supervisory control system for humanoid robot motion planning. The proposed system is a supervisory structure formed by two hierarchical levels of a discrete event system. The high level system is represented by a Petri net. This Petri net behaves as a supervisor that indicates the sequence of motions that the robot has to make. A robot walking in a closed space forms the ...

2014
Prases K. Mohanty Dayal R. Parhi

Nowadays intelligent tools such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable methods for modeling an engineering system. This paper presents a new hybrid technique based on the combination of fuzzy inference system and artificial neural network for addressing navigational proble...

2015
Dinesh G Harkut

A real-time operating system (RTOs) is often used in embedded system, to structure the application code and to ensure that the deadlines are met by reacting on events by executing the functions within precise time. Most embedded systems are bound to real-time constraints with determinism and latency as a critical metrics. RTOs are generally implemented in software, increases computational overh...

Journal: :IEEE Trans. Fuzzy Systems 2001
Serge Guillaume

Fuzzy inference systems (FIS) are widely used for process simulation or control. They can be designed either from expert knowledge or from data. For complex systems, FIS based on expert knowledge only may suffer from a loss of accuracy. This is the main incentive for using fuzzy rules inferred from data. Designing a FIS from data can be decomposed into two main phases: automatic rule generation...

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