Fuzzy inference systems have been applied in recent years in various medical fields due to their ability to obtain good results featuring white-box models. Adaptive Neuro-Fuzzy Inference System (ANFIS), which combines adaptive neural network capabilities with the fuzzy logic qualitative approach, has been previously used in modelling survival of breast cancer patients based on patient groups de...

The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to each modeling step, able to lead us to an optimal neural network forecasting tool. In order to underline the effects of users’ decision making on the ...

This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number o...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...

An enhanced approach for network monitoring is to create a network monitoring tool that has artificial intelligence characteristics. There are a number of approaches available. One such approach is by the use of a combination of rule based, fuzzy logic and neural networks to create a hybrid ANFIS system. Such system will have a dual knowledge database approach. One containing membership functio...

An intelligent learning-based approach using neural network and fuzzy logic to the problem of interference canceling is proposed in the paper. The famous signal-processing structure of adaptive noise canceling is used for the research of interference signal canceling, in which a neuro-fuzzy system is used as the adaptive notch filter. Four T-S fuzzy rules are in the neuro-fuzzy filter. The filt...

today, dc motors is still being used globally due to their easy speed controllability. in this article, an adaptive neuro-fuzzy inference system (anfis) controller is designed for dc motors. the main purpose of performing such task is to reduce the dc motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

The systemic nature of the risk bankruptcy financial institutions has become an important issue in maintaining existence and stability domestic global finance. use statistics for prediction so far provides optimal benefits. However, this approach limitations, especially since model is built based on systematic relationships, linearity normality aspects are often weaknesses. This can be overcome...

Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  First,...