QSPR model for the forecast of dynamic viscosity  of arenas by the topological characteristics of molecules

Prediction of the dynamic viscosity of saturated hydrocarbons vapors is an important step in the calculation of various processes and apparatuses in chemical technology. In order to quickly determine the dynamic viscosity without resorting to the use of expensive equipment, methods of mathematical modeling are currently used. To predict the dynamic viscosity of saturated arenas vapors, a nonlinear multivariate regression model QSPR is proposed. The model associates with a dynamic viscosity a set of descriptors – the topological characteristics of molecular graphs: the Randic index, the Wiener index, and also the functions of the eigenvalues of the topological matrix of the molecule, which reflect the main structural and chemical factors, such as branching, length of the carbon skeleton and energy parameters of molecules, for example, Hückel’s perturbation spectrum of molecules, as well as affecting dynamic viscosity. The objects of research used arenas. The studied sample included 40 hydrocarbons of a number of arenas. The proposed model adequately describes the dynamic viscosity of saturated arenas vapors. The coefficient of determination of the model is 0.986. The average absolute and relative error for the test sample of HF is -2.46⋅10-7 cP and 1.83%, respectively. The model is applicable for engineering and scientific forecasts of the dynamic viscosity of various saturated arenas vapors.

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Prediction of octane numbers of substituted alkanes according to the topological characteristics of the molecules

Butlerov Communications ◽

10.37952/roi-jbc-01/19-59-7-69 ◽

2019 ◽

Vol 59 (7) ◽

pp. 69-75

Author(s):

Oleg S. Koledin ◽

◽

Ella A. Kovaleva ◽

Mikhail Yu. Dolomatov ◽

Svetlana A. Arslanbekova ◽

...

Keyword(s):

Octane Number ◽

Motor Fuel ◽

Wiener Index ◽

Test Sample ◽

Coefficient Of Determination ◽

Proposed Model ◽

Octane Rating ◽

Chemical Factors ◽

Topological Characteristics ◽

Substituted Alkanes

There may occur a special mode of combustion of the fuel-air mixture called detonation, when using motor fuel with a low octane rating. Methods of mathematical modeling are currently used to quickly determine octane numbers without using of expensive equipment. A nonlinear multidimensional QSPR regression model is proposed to predict the octane number of normal and substituted alkanes-gasoline components. The model associates octane numbers with a set of descriptors (topological characteristics of molecular graphs): the Randic index, the Wiener index, and the functions of the eigenvalues of the topological matrix of the molecule, reflecting the main structural and chemical factors, such as branching, the length of the carbon structure and the energy parameters of the molecules, for example perturbation of Hückel spectrum of molecules, as well as affecting octane numbers. The substituted alkanes were used as research objects. A studied sample included 36 hydrocarbons from the homolologus serious of substituted alkanes. The proposed model adequately describes the octane number of alkanes. The coefficient of determination of the model is 0.972. The model was tested on 19 substances which were not included in the base series. The average, absolute and relative error for the test sample of octane numbers were 1.5 units and 2.7% respectively. The model is applicable for engineering and scientific forecasts of octane numbers of various alkanes in motor fuel.

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Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

Sustainability ◽

10.3390/su13073727 ◽

2021 ◽

Vol 13 (7) ◽

pp. 3727

Author(s):

Fatema Rahimi ◽

Abolghasem Sadeghi-Niaraki ◽

Mostafa Ghodousi ◽

Soo-Mi Choi

Keyword(s):

Regression Analysis ◽

Mean Squared Error ◽

Population Distribution ◽

Temporal Distribution ◽

Coefficient Of Determination ◽

Temporal Modeling ◽

Location Data ◽

Time Period ◽

Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

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An Interpretable Extreme Gradient Boosting Model to Predict Ash Fusion Temperatures

Minerals ◽

10.3390/min10060487 ◽

2020 ◽

Vol 10 (6) ◽

pp. 487

Author(s):

Maciej Rzychoń ◽

Alina Żogała ◽

Leokadia Róg

Keyword(s):

Coefficient Of Determination ◽

Gradient Boosting ◽

Important Indicator ◽

Upper Silesian Coal Basin ◽

Proposed Model ◽

Extreme Gradient Boosting ◽

The Impact ◽

Partial Dependence ◽

Individual Input

The hemispherical temperature (HT) is the most important indicator representing ash fusion temperatures (AFTs) in the Polish industry to assess the suitability of coal for combustion as well as gasification purposes. It is important, for safe operation and energy saving, to know or to be able to predict value of this parameter. In this study a non-linear model predicting the HT value, based on ash oxides content for 360 coal samples from the Upper Silesian Coal Basin, was developed. The proposed model was established using the machine learning method—extreme gradient boosting (XGBoost) regressor. An important feature of models based on the XGBoost algorithm is the ability to determine the impact of individual input parameters on the predicted value using the feature importance (FI) technique. This method allowed the determination of ash oxides having the greatest impact on the projected HT. Then, the partial dependence plots (PDP) technique was used to visualize the effect of individual oxides on the predicted value. The results indicate that proposed model could estimate value of HT with high accuracy. The coefficient of determination (R2) of the prediction has reached satisfactory value of 0.88.

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Determination of the Super-Elliptic Shape of Tire-Soil Contact Area Using Image Processing Method

Cercetari Agronomice in Moldova ◽

10.1515/cerce-2015-0026 ◽

2015 ◽

Vol 48 (2) ◽

pp. 5-14

Author(s):

R. Farrokhi Teimourlou ◽

H. Taghavifar

Keyword(s):

Image Processing ◽

Contact Area ◽

Block Design ◽

Processing Method ◽

Coefficient Of Determination ◽

Inflation Pressure ◽

Wheel Load ◽

Image Processing Method ◽

Proposed Model

Abstract The present study is aimed at determination of the super-elliptic shape of tire-soil contact area using image processing method. Contact area has a substantial role on determination of soil compaction and tractive parameters of agricultural tractors. A very well-known model in this realm is to describe the contact area with superellipse geometry. A soil bin testing facility equipped with a single-wheel tester was utilized to conduct the needed experiments. The experiments were carried out at three levels of wheel load, three levels of tire inflation pressure with three replicates in a completely randomized block design. Corresponding images were taken for each of the experiments and the images were processed accordingly. The contact length and width were determined using imdistline command in MATLAB commercial software. This experiment was conducted at three levels of wheel load (2, 3, and 4 kN), and three levels of tire inflation pressure (100, 200, and 300 kPa) with three replications. The aforementioned parameters were applied consequently in the superellipse model and the contact area was computed. The obtained results disclosed that increase of wheel load increases the contact area. Contradictory, increment of tire inflation pressure reduces the formed contact area. Additionally, the potential of contact area determination with the proposed model was compared with that of actual values, which denoted coefficient of determination equal to 0.96, which shows the promising ability of the proposed model and the appropriateness of describing contact area with superellipse geometry

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