it is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. hence, at present study, two models including artificial neural networks and nonlinear multivariate regression were used to predict peak discharge in taleghan watershed. maximum daily mean discharge and corresponding daily rainfall, one day antecedent and...

Fruit classification is found to be one of the rising fields in computer and machine vision. Many deep learning-based procedures worked out so far classify images may have some ill-posed issues. The performance scheme depends on range captured images, volume features, types characters, choice features from extracted type classifiers used. This paper aims propose a novel learning approach consis...

In the oil industry, productivity of wells depends on performance sub-surface equipment system. These systems often have problems stemming from sand, corrosion, internal pressure variation, or other factors. order to ensure high and avoid high-cost losses, it is essential identify source possible failures in early stage. However, this requires additional maintenance fees human power. Moreover, ...

abstract in the present study, agricultural sector import was forecasted by using the econometric and the ann methods. import data from 1971 to 2004 and 2004-2009 was used for forecasting, network training and testing forecast accuracy, respectively. the results shown that feed-forward neural network has much less error and better performance than the arima and the var methods. on the basis of ...

Multilayered feed-forward neural networks trained with back-propagation algorithm are one of the most popular “online” artificial neural networks. These networks are showing strong inherit parallelism because of the influence of high number of simple computational elements. So it is natural to try to implement this kind of parallelism on parallel computer architecture. The Parallel Hybrid Ring ...

In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical ...

A mention may or may not be coreferred elsewhere in the document. Identifying those mentions that are corefered (called coreferents) is an important step in many NLP tasks, like coreference resolution. To classify a mention as singleton or coreferent using just one sentence is a challenging problem, but previous work suggests that there are cues in a sentence which can be used to predict if a m...

In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical ...

Energy performance analysis in buildings is becoming more and highlighted, due to the increasing trend of energy consumption building sector. Many studies have declared great potential soft computing for this analysis. A particular methodology sense employing hybrid machine learning that copes with drawbacks single methods. In work, an optimized version a popular model, namely feed-forward neur...

Adverse conditions within specific offshore environments magnify the challenges faced by a vessel’s energy-efficiency optimization in Industry 4.0 era. As data rate and volume increase, analysis of big using analytical techniques might not be efficient, or even infeasible some cases. The purpose this study is development deep-learning models that can utilized to predict propulsion power vessel....