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...

This paper presents a new interval type-2 fuzzy inference system to handle uncertainty using reduced-set vector learning mechanism based on hybrid kernels. Firstly, a novel concept, interval kernel, is proposed. It establishes a relationship between interval type-2 fuzzy membership and hybrid kernel. According to it, a particular interval type-2 fuzzy inference system is built, which abandons t...

1 This work is supported by national natural science foundation of China, No.60475036. Abstract –The noise detection model is build up by using SVM-based fuzzy inference system for detecting the impulse noise in an image. The support vectors which are used to confirm the fuzzy basis function and create the corresponding fuzzy rules are extracted from the training samples by the learning mechani...

many factors affect yield loss in wheat harvesting with a grain combine harvester and there is no mathematical model to describe the behavior of this complex system. thus in this study, a fuzzy logic controller (flc) was designed, implemented and tested for the automatic settings of cylinder speed, concave clearance, fan speed and forward speed of a model 955 john deere combine. first, the mech...

Introduction: In radiotherapy with external surrogates, exact information of tumor position is one of the key factors that improves treatment delivery. Many dynamic tumors in thorax region of patient move mainly due to respiration and are known as intra-fractional motion error that must be compensated, as well. One of clinical strategy is using Stereotactic Body Radiation Thera...

Fuzzy inference models can conduct advanced inference using knowledge which is easily understood by humans. In this paper, we propose a leaning fuzzy inference model. The model can learn with experience data obtained by trial-and-error of a task. The learning of the model is executed after each trial of the task. Hence, it is expected that the achievement rate increases with repetition of the t...

Wave height as well as water depth at the breaking point are two basic parameters which are necessary for studying coastal processes. In this study, the application of soft computing-based methods such as artificial neural network (ANN), fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS) and semi-empirical models for prediction of these parameters are investigated. Th...

The fuzzy rule based inference is known to be a useful tool to capture the behavior of an approximate system in transportation. One of the obstacles of implementing the fuzzy rule based inference, however, has been to calibrate the membership functions of the fuzzy sets used in the rules. This paper proposes a way to calibrate the membership function when a set of input and output data is given...

this paper describes the development of a fuzzy decision support system (fdss) for the assessment of risk in e-commerce (ec) development. a web-based prototype fdss is suggested to assist ec project managers in identifying potential ec risk factors and the corresponding project risks. a risk analysis model for ec development using a fuzzy set approach is proposed and incorporated into the fdss....