The gross calorific value (GCV) or heating value of a sample of fuel is one of the important properties which defines the energy of the fuel. Many researchers have proposed empirical formulas for estimating GCV value of coal. There are some known methods like Bomb Calorimeter for determining the GCV in the laboratory. But these methods are cumbersome, costly and time consuming. In this paper, m...

the gross calorific value (gcv) or heating value of a sample of fuel is one of the important properties which defines the energy of the fuel. many researchers have proposed empirical formulas for estimating gcv value of coal. there are some known methods like bomb calorimeter for determining the gcv in the laboratory. but these methods are cumbersome, costly and time consuming. in this paper, m...

Various ways of approach, to determine the horizontal distribution trend (tendency) of Chromium (Cr) in soil, where is high pollution by this element are analysed. Polynominal regression algorithms (I, II, III degree polynominals), interpolation algorithms (TIN, Kriging, RST), and also artificial neural networks (MLP, CANFIS, RBF, GRNN, PNN, MDN) are applied. Data from field experiments, carrie...

(2002) Intelligent diagnosis of rotating machinery faults-A review. The task of condition monitoring and fault diagnosis of rotating machinery faults is both significant and important but is often cumbersome and labour intensive. Automating the procedure of feature extraction, fault detection and identification has the advantage of reducing the reliance on experienced personnel with expert know...

AbstrAct A Web-based fabric database is introduced in terms of its physical structure, software system architecture , basic and intelligent search engines, and various display methods for search results. A fuzzy linear clustering method is used to predict fabric drape coefficient from fabric mechanical and structural properties. Experimental data indicate that fuzzy linear clustering is quite e...

Abstract This paper enters the ongoing volatility forecasting debate by examining ability of a wide range Machine Learning methods (ML), and specifically Artificial Neural Network (ANN) models. The ANN models are compared against traditional econometric for ten Asian markets using daily data time period from 12 September 1994 to 05 March 2018. empirical results indicate that ML algorithms, acro...

This study, fundamentals of fuzzy block theory, and its application in assessment of stability in underground openings, has surveyed. Using fuzzy topics and inserting them in to key block theory, in two ways, fundamentals of fuzzy block theory has been presented. In indirect combining, by coupling of adaptive Neuro Fuzzy Inference System (NFIS) and classic block theory, we could extract possibl...