movement of sediment in the river causes many changes in the river bed. these changes are called bedform. river bedform has significant and direct effects on bed roughness, flow resistance, and water surface profile. thus, having adequate knowledge of the bedform is of special importance in river engineering. several methods have been developed by researchers for estimation of bed form dimensio...

This paper proposes a new type of a support vector machine which uses a kernel constituted from fuzzy basis functions. The proposed network combines the characteristics both of a support vector machine and a fuzzy system: high generalization performance, even when the dimension of the input space is very high, structured and numerical representation of knowledge and ability to extract linguisti...

As part of an effort to develop intelligent agriculture, new methods for enhancing the quality vegetables are being continually developed. In recent years, Convolutional Neural Network (CNN) has shown be most successful and extensively used approach identifying pre-trained vegetables. However, this method is time-consuming due scarcity truly large, significant datasets. Using a CNN model as fea...

Most of existing researches for multi response optimization are based on regression analysis. However, the artificial neural network can be applied for the problem. In this paper, two approaches are proposed by consideration of both methods. In the first approach, regression model of the controllable factors and S/N ratio of each response has been achieved, then a fuzzy programming has been app...

Image classification is elementary step of the remote sensing applications, which is to extract useful geographic information from raw image data. Many new methods for remote sensed image classification have been developed such as machine learning, support vector machine (SVM), neural network classifier, fuzzy set, genetic algorithm and Artificial intelligence. Though these method may have high...

Moving object recognition by shapebased neural fuzzy network is proposed in this paper. The moving objects considered in this paper include pedestrians, cars, motorcycles, and dogs. Given the shape of the moving object, we calculate its contour. The distance between the contour center and each contour point is calculated and smoothed. Parts of the feature vectors are obtained from discrete Four...

In neural network the connection strength of each neuron is updated through learning. Through repeated simulations of crisp neural network, we propose the idea that for each neuron in the network, we can obtain reduced model with more efficiency using wavelet based multiresolution analysis (MRA) to form wavelet based quasi fuzzy weight sets (WBQFWS). Such type of WBQFWS provides good initial so...

The objective of this study is to build a fuzzy linguistic prediction model (FLPM) for analyzing the actuation duration of acute hyperglycemia to sinoatrial node field potential. The field potential was recorded using microelectrode arrays (MEA). The experimental data were analyzed using partial least squares (PLS), support vector machine (SVM), back propagation neural network (BPNN) and the pr...

This paper investigates the potential of support vector machines based regression approach to model the local scour around bridge piers using field data. A dataset of consisting of 232 pier scour measurements taken from BSDMS were used for this analysis. Results obtained by using radial basis function and polynomial kernel based Support vector regressionwere comparedwith four empirical relation...

ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...