In this paper, a differential protection schemes using fuzzy inference system (FIS) for power transformer protection is presented. First we review the concept of differential protection, and illustrate the magnetizing inrush current as they belong to the causes of the protection maloperation. Then relay logic and the algorithm that uses Discreet Fourier transformer for extraction of fundamental...

In the present study, the adaptive neuro-fuzzy inference system (ANFIS) is developed for the prediction of effective thermal conductivity (ETC) of different fillers filled in polymer matrixes. The ANFIS uses a hybrid learning algorithm. The ANFIS is a class of adaptive networks that is functionally equivalent to fuzzy inference systems (FIS). The ANFIS is based on neuro-fuzzy model, trained wit...

Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It...

Background and objectives: The kidneys of chronic kidney disease (CKD) patients do not have enough function and hemodialysis (HD) is a common procedure for their treatment. HD requires vascular access surgery (VAS) and arteriovenous fistula (AVF) is a low-complication method in VAS. However, different rates of AVF failure have been reported worldwide which can cause repeating s...

The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in inference systems (FIS) development. However, researchers highlight different challenges issues this FIS development because its complexity. This paper evaluates the current state art complexity Computer Science, Software Engineering Information Systems, specifically: 1) What exi...

A Fuzzy Inference System was developed to aid in the diagnosis of Pulmonary Embolism using ventilation-perfusion scans and correlated chest x-rays. The diagnosis achieved needed to be accurate and reliable, comparable to that of a nuclear medicine radiologist. The Mamdani fuzzy model has been employed to implement the inference system. Sources of expertise included the criteria defined by PIOPE...

In this paper the development of a model for Mamdani type fuzzy rule-based systems using the new concept of granular computing (GrC) is presented. In this study a GrC algorithm is used to capture the required information in the form of data granules within a high dimensional complex database. The initial collection of information granules is used as a rule-base for a fuzzy inference system (FIS...

In this work the recently developed fuzzy logic-based adaptive Kalman filter (FL-AKF) is used to build adaptive centralized, decentralized, and federated Kalman filters for Adaptive MultiSensor Data Fusion (AMSDF). The adaptation carried out is in the sense of adaptively adjusting the measurement noise covariance matrix of each local FL-AKF to fit the actual statistics of the noise profiles pre...

Building a Fuzzy Inference System (FIS) generally requires experts’ knowledge. However, experts’ knowledge is not always available. When there is few experts’ knowledge, it becomes hard to build a FIS using one of supervised learning methods. Meanwhile, Q-learning is a kind of reinforcement learning where an agent can acquire knowledge from its experiences even without the model of the environm...