Volatility forecasting is an important process required to measure variability in equity prices, risk management, and several other financial activities. Generalized autoregressive conditional heteroscedastic methods <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$(\textit{GARCH})$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mo stretchy="false">(</mo> <mi mathvariant="italic">GARCH</mi> <mo stretchy="false">)</mo> </mrow> </math> </EquationSource> </InlineEquation> have been used to forecast volatility...</equationsource></equationsource></inlineequation>

Evolutionary Algorithms (EAs) are emerging as competitive and reliable techniques for several optimization tasks. Juxtapositioning their higher-level and implicit correspondence; it is provocative to query if one optimization algorithm can benefit from another by studying underlying similarities...

This paper presents an economical evaluation and parametric optimization on subcritical ORC (organic Rankine cycle) system for recovering the low-temperature waste heat of flue gas which is released from industrial boilers. First, the effects of the PPTD (pinch point temperature difference) in...