Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited reserves and developing a useful abstraction management strategy. The purpose this study was to assess the predictive accuracy estimation capability various models based on Adaptive Neuro Fuzzy Inference System (ANFIS). These included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimizatio...

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of EEG signals were us...

In the primary and final designs of projects related to rock mechanics engineering geology, one key parameters that needs be taken into account is intact elastic modulus (E). To measure this parameter in a laboratory setting, core samples with high-quality costly tools are required, which also makes for time-consuming process. The aim study assess effectiveness two meta-heuristic-driven approac...

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...

In India, the first confirmed case of novel corona virus (COVID-19) was discovered on January 30, 2020. The number cases is increasing day by day, and it crossed 21,53,010 August 9, this paper, a hybrid forecasting model has been proposed to determine for upcoming 10 days based earlier found in India. adaptive neuro-fuzzy inference system (ANFIS) mutation-based Bees Algorithm (mBA). meta-heuris...

This study deals with predicting the performance of an evaporative condenser using both artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) techniques. For this aim, an experimental evaporative condenser consisting of a copper tube condensing coil along with air and water circuit elements was developed and equipped with instruments used for temperature, pressure an...

An e cient methodology is proposed to optimize space trusses considering geometric nonlinearity. The optimization task is performed by a continuous Particle Swarm Optimization (PSO). Design variables are cross sectional areas of the trusses and their weights are also taken as the objective function. Design constraints are de ned to restrict nodal displacements and element stresses and prevent t...

Resumen. El presente artículo muestra los resultados obtenidos al aplicar redes neuronales y el modelo neurodifuso ANFIS para la predicción de caudales medios diarios en una sección de la cuenca del Amazonas. Se aplicaron los pasos que componen la metodología KDD Knowledge Discovery in Databases sobre la información hidrológica recolectada de las estaciones del servicio de observación SO HYBAM ...

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...

This paper investigates the effectiveness of four different soft computing methods, namely radial basis neural network (RBNN), adaptive neuro fuzzy inference system (ANFIS) with subtractive clustering (ANFIS-SC), ANFIS with fuzzy c-means clustering (ANFIS-FCM) and M5 model tree (M5Tree), for predicting the ultimate strength and strain of concrete cylinders confined with fiber-reinforced polymer...