Abstract Accurate modeling and prediction of suspended sediment load (SSL) in rivers have an important role environmental science design engineering structures are vital for watershed management. Since different parameters such as rainfall, temperature, discharge with the lag times significant effects on SSL, quantifying understanding nonlinear interactions dynamics has always been a challenge....

background: we aimed to assess the high-risk group for suicide using different classification methods includinglogistic regression (lr), decision tree (dt), artificial neural network (ann), and support vector machine (svm). methods: we used the dataset of a study conducted to predict risk factors of completed suicide in hamadan province, the west of iran, in 2010. to evaluate the high-risk grou...

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...

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

In this paper, an efficient node-level target classification scheme in wireless sensor networks (WSNs) is proposed. It uses acoustic and seismic information, and its performance is verified by the classification accuracy of vehicles in a WSN. Because of the hard limitation in resources, parametric classifiers should be more preferable than non-parametric ones in WSN systems. As a parametric cla...

Currently, limit-checking on telemetry sensor data of a spacecraft is widely used to detect its faults and anomalous behavior. Since classical limit-checking usually considers only a priori fixed pair of upper and lower bounds for each sensor variable, it sometimes fails to detect phenomena that are anomalous only in certain operating modes. To handle this problem, we present a method to predic...

Abstract Precise and credible runoff forecasting is extraordinarily vital for various activities of water resources deployment implementation. The neoteric contribution the current article to develop a hybrid model (ANFIS-GPR) based on adaptive neuro-fuzzy inference system (ANFIS) Gaussian process regression (GPR) monthly in Beiru river China, optimal input schemes models are discussed detail. ...

Precise forecasting of reference evapotranspiration (ET0) is one the critical initial steps in determining crop water requirements, which contributes to reliable management and long-term planning world’s scarce sources. This study provides daily prediction multi-step forward ET0 utilizing a long short-term memory network (LSTM) bi-directional LSTM (Bi-LSTM) model. For predictions, model’s accur...

Primljeno (Received): 2011-10-10 Prihvaćeno (Accepted): 2012-01-22 Original scientific paper The paper summarizes the results of investigations on the conductive silicone rubber as strain sensor and presents a segment of the project for developing the new principle of a universal gripper with adaptable shape morphing surfaces. An experimental investigation of the sensors subjected to different ...