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 ...

This paper discusses the technology of extracting the chemical knowledge from the structured electronic sources, problem-oriented systems of science data analytics, and methods of science data analysis. Application of the feed-forward artificial neural network for predicting the reactivity of a compound (the classical potential barrier) in reactions of hydrocarbons with hydrogen atom in solutio...

An artificial Neural Network (ANN) is a well known universal approximator to model smooth and continuous functions (Brown & Harris, 1994). As ANNs can realize nonlinear models, they are flexible in modeling a wide variety of real-world complex applications, such as handwriting recognition, speech recognition, fault detection, medical inspection (Zhang, 2000), etc. ANNs being applied for pattern...

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....