Many complexes of 3,5-dimethyl-1H-pyrazol-1-yl phenyl methanone with Cr(III), Co(II), Ni(II), Cu(II) and Cd(II) were synthesized and characterized by FT-IR, UV/visible spectra, elemental analysis, room temperature magnetic susceptibility and molar conductivity. Cd(II) complex was expected to have tetrahedral structure while all the other complexes were expected to have an octahedral structure.

The New Schiff base ligand 4,4'-[(1,1'-Biphenyl)-4,4'-diyl,bis-(azo)-bis-[2-Salicylidene thiosemicarbazide](HL)(BASTSC)and its complexes with Co(II), Ni(II), and Cu(II) were prepared and characterized by elemental analysis, electronic, FTIR, magnetic susceptibility measurements. The analytical and spectral data showed, the stiochiometry of the complexes to be 1:1 (metal: ligand). FTIR spectral data showed that the ligand behaves as dibasic hexadentate molecule with (N, S, O) donor sequence towards metal ions. The octahedral geometry for Co(II), Ni(II), and Cu(II) complexes and non electrolyte behavior was suggested according to the analysis data.

The phenyl hydrazine was react readily with acetic acid chloride in [1:2] ratio in alkyl of ethanolic solution, and refluxe for five hours to produce a new ligand of (N-Carboxymethyl-N-phenyl-hydrazino)-acetic acid [H2L].

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h