In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The new ligand [N1,N4-bis((1H-benzo[d]Glyoxalin-2-yl)carbamothioyl)Butanedi amide] (NCB) derived from Butanedioyl diisothiocyanate with 2-aminobenz imidazole was used to prepare a chain of new metal complexes of Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Ag(I), Cd(II) by general formula [M(NCB)]Xn ,Where M= Cr(III), n=3, X=Cl; Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Cd(II) ,n=2 , X=Cl; Ag(I), n=1, X=NO3. Characterized compounds on the basis of 1H, 13CNMR (for (NCB), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H, %N and %S, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA),while its corrosion inhibition for mild steel in Ca(OH)2 solution is studied by weight loss. These measureme

A novel series of mixed-ligand complexes of the type, [ML 1 (L 2 ) 3 ]Cl x [M = Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiffbase (HL 1 ) as main ligand, nicotinamide (L 2 ) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL 1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR, 1 H-NMR, 13 C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiffbase ligand, HL 1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxy- gen atom