In order to characterize the behavior of nonlinear dynamic systems many different approaches have been proposed in recent years. One of the best black-box models employed to deal with system nonlinearities is the combination of artificial neural network (ANN) and fuzzy logic system (FLS), which is known as neuro-fuzzy system. However, the gradient-based nature of this combination causes some de...

Soft computing can be used to build hybrid intelligent systems for achieving different goals in real-world applications. Soft Computing techniques include, at the moment, fuzzy logic, neural networks, genetic algorithms, chaos theory methods, and similar techniques that have been proposed in recent years. Each of these techniques has advantages and disadvantages, and several real-world problems...

This paper presents a new hybrid neuro-fuzzy model which is capable of learning structure and parameters by means of recursive binary space partitioning BSP. Introduction Neuro-fuzzy systems (NFSs) [1] combine the learning ability of artificial neural nets (ANNs) with the linguistic interpretation capacity of fuzzy inference systems (FISs) [2]. This work makes use of BSP (Binary Space Partition...

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM ...

This paper describes the computational automatic supply chain configuration (SCC) based on fuzzy logic prediction actualizing automatically the chain stages considering different customer service level petitions. Each level is selected in accordance with the inference and the knowledge base process supplies (KBPS). The SCC model as an intelligent processes selector (IPS), allows dynamical confi...

This paper deals with static hysteresis modeling for the PAM-based (pneumatic artificial muscles) position servosystem by means of an adaptive neuro-fuzzy inference system. The hysteretic behavior is expressed in arm position-pressure difference dependence where the output variable (arm position) depends on the history of input variable (pressure difference). In this way, a first order (until i...

In this paper, a neural fuzzy system for the diagnosis of potassium disturbances is presented. This paper develops an adaptive neuro-fuzzy expert system that can provide accurate diagnosis of potassium disturbances. The proposed diagnostic approach has many attractive features. First, it provides an efficient tool for diagnosis of K+ disturbances and aids clinicians, especially the non-expert o...

Vertical handover based on the single criteria decision may cause inefficient handoff therefore multi-criteria handoff is gaining significance due to the enhancements brought by the mobility models in Fourth Generation (4G) technologies. Since the complexity and processing of multicriteria during handover is a complex job requiring high handover time leading to the high packet loss and even bre...

The aim of this paper is to present and compare four different neuro-fuzzy approaches to the construction of fuzzy rule-based models for dynamic processes. These approaches have been applied to modelling of an industrial gas furnace system (Box-Jenkins benchmark). The following neuro-fuzzy systems have been considered: nfMod – the system proposed in this paper, the well-known ANFIS and NFIDENT ...