Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

The effect of polyacrylic acid on the surface properties of calcite and fluorite aiming at their selective flotation

Zhang C., Gao Z., Hu Y., Sun W., Tang H., Yin Z., He J., Guan Q., Zhu Y.

Physicochemical Problems of Mineral Processing

2018

Vol. 54, iss. 3

868--877

In this study, the polyacrylic acid (PAA) was studied as a selective depressant for calcite in the selective flotation of fluorite and calcite, and the implications of this process for the separation of fluorite ore were studied using micro-flotation tests, and the results were analyzed with Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) analyses. The flotation tests indicated that the preferential adsorption of PAA onto calcite rather than sodium oleate (NaOl) could selectively depress the flotation of calcite, allowing its separation from fluorite at pH 7. The zeta potential of calcite became more negative with the addition of PAA rather than with NaOl. However, the characteristic features of PAA adsorption were not observed for fluorite, suggesting that NaOl preferentially adsorbed on the surface of fluorite, or that PAA could be replaced by NaOl on the fluorite surface. FT-IR and XPS analysis were utilized to obtain a better understanding of the mechanism by which PAA was more strongly adsorbed on the calcite surface than NaOl. This was revealed to occur through chemical bonding between the carboxyl group of PAA and the hydroxyl groups of the Ca species on the calcite surface, modifying the structure of the adsorbed layer. A possible adsorption mechanism, along with a postulated adsorption mode for the surface interaction between PAA and calcite, is proposed.

An analysis of the performance of genetic programming for realised volatility forecasting

Yin Z., O’Sullivan C., Brabazon A.

Journal of Artificial Intelligence and Soft Computing Research

2016

Vol. 6, No. 3

155--172

Traditionally, the volatility of daily returns in financial markets is modeled autoregressively using a time-series of lagged information. These autoregressive models exploit stylised empirical properties of volatility such as strong persistence, mean reversion and asymmetric dependence on lagged returns. While these methods can produce good forecasts, the approach is in essence atheoretical as it provides no insight into the nature of the causal factors and how they affect volatility. Many plausible explanatory variables relating market conditions and volatility have been identified in various studies but despite the volume of research, we lack a clear theoretical framework that links these factors together. This setting of a theory-weak environment suggests a useful role for powerful model induction methodologies such as Genetic Programming (GP). This study forecasts one-day ahead realised volatility (RV) using a GP methodology that incorporates information on market conditions including trading volume, number of transactions, bid-ask spread, average trading duration (waiting time between trades) and implied volatility. The forecasting performance from the evolved GP models is found to be significantly better than those numbers of benchmark forecasting models drawn from the finance literature, namely, the heterogeneous autoregressive (HAR) model, the generalized autoregressive conditional heteroscedasticity (GARCH) model, and a stepwise linear regression model (SR). Given the practical importance of improved forecasting performance for realised volatility this result is of significance for practitioners in financial markets.

Behavior Consistency Analysis Based on the Behavior Profile about Transition Multi-Set of Petri Net

Fang X., Wang M., Yin Z.

Przegląd Elektrotechniczny

2013

R. 89, nr 1b

171--173

Duplicate activities often appear in the business process modeling, analyzing the consistency of corresponding model containing duplicate activities is a problem , the existing behavior consistency methods can not analyze effectively the process model with the multi-set of transition. In the paper, by analyzing of three kinds of weak order relations of multi set of transition, a kind of consistency measure methods based on behavior profile of multi-sets of transitions of Petri net is proposed. Finally , an example is given out, which shows the method is effective.

W artykule przedstawiono metodę określenia regularności związków słabych w systemie wielowątkowym o powielających się danych. Analiza, trzech wybranych rodzajów relacji oparta została na profilu wielowątkowej sieci Petriego. Opisano także przykład, potwierdzający skuteczność działania.