Deep learning-based predictive models for forex market trends: Practical implementation and performance evaluation.

In recent years, there has been growing interest in the prediction of financial market trends, due to its potential applications in the real world. Unlike traditional investment avenues such as the stock market, the foreign exchange (Forex) market revolves around two primary types of orders that correspond with the market's direction: upward and downward. Consequently, forecasting the behaviour of the Forex behaviour market can be simplified into a binary classification problem to streamline its complexity.

Equilibria of semi-volatile isothiazolinones between air and glass surfaces measured by gas chromatography and Raman spectroscopy.

Trace amounts of semi-volatile organic compounds (SVOCs) of the two isothiazolinones of 2-methylisothiazol-3(2H)-one (MIT) and 2-octyl-4-isothiazolin-3-one (OIT) were detected both in the air and on glass surfaces. Equilibria of SVOCs between air and glass were examined by solid phase microextraction-gas chromatography/mass spectrometry (SPME-GC/MS). Surface to air distribution ratios of K for MIT and OIT were determined to be 5.

Optimal control of a fractional order model for granular SEIR epidemic with uncertainty.

In this study, we present a general formulation for the optimal control problem to a class of fuzzy fractional differential systems relating to SIR and SEIR epidemic models. In particular, we investigate these epidemic models in the uncertain environment of fuzzy numbers with the rate of change expressed by granular Caputo fuzzy fractional derivatives of order  ∈ (0, 1]. Firstly, the existence and uniqueness of solution to the abstract fractional differential systems with fuzzy parameters and initial data are proved.

Linear quadratic regulator problem governed by granular neutrosophic fractional differential equations.

Quadratic cost functions estimation in the linear optimal control systems governed by differential equations (DEs) or partial differential equations (PDEs) has a well-established discipline in mathematics with many interfaces to science and engineering. During its development, the impact of uncertain phenomena to objective function and the complexity of the systems to be controlled have also increased significantly. Many engineering problems like magnetohydromechanical, electromagnetical and signal analysis for the transmission and propagation of electrical signals under uncertain environment can be dealt with.