Cosine Of Angle Research Articles

The use of interphacial energies to estimate the spreading coefficients of organic liquids by the solid polymer surface of polytetrafluoroethylene

In the article, using equations previously obtained by the author, calculations were made of the interfacial energies of a solid polymer – polytetrafluoroethylene in contact with organic liquids and their vapors. Based on the calculation results, the spreading coefficients in the studied systems were calculated. Since Young’s derivation of the equation for the cosine of the contact angle, many researchers have attempted to determine the surface energy of solids, which would, in turn, make it possible to determine the interfacial energy at the solid-melt (liquid) interface. However, on the way to solving this problem there were obstacles associated with various processes that accompany phenomena occurring on the surface of a solid body in the presence of a liquid (melt) of another body on its surface. This is not the place to list all types of processes. They are well known to specialists in the field of surface phenomena. Here are just a few of them that affect the surface properties of bodies: chemical reactions, mutual dissolution of components of solid and liquid phases, deformation of solid phases, etc. In the case of contact of the polymer with organic liquids, such obstacles do not exist. Also, since it is impossible to dwell on all publications devoted to the determination of the surface energy of solids, the article discusses specific works on determining the interfacial energy at contact angles close to or equal to zero. Since the question of the behavior of interfacial energy at a contact angle equal to zero is of fundamental importance, and there are conflicting opinions in the literature on this matter, giving the correct answer to this question is an urgent task. Using examples of calculations of interfacial energies of homologous series of organic liquids on a solid surface of polytetrafluoroethylene, we have shown that only at zero contact angle the interfacial energy is zero. In this article, using interfacial energy values, we are the first to calculate the spreading coefficients of organic liquids over the surface of a solid polymer, which, in our opinion, is also an urgent task.

Bifacial and Angular‐Resolved Performance Characterization of Ultrathin Cu(In,Ga)Se2 Solar Cells Including Nanostructures

Bifacial solar cells experience growing interest not just for crystalline silicon photovoltaic modules. Thin‐film solar cells deposited on a transparent back contact bring inherent semitransparency, making them ideally suited for bifacial applications. Herein, a systematic investigation of bifacial measurement procedures is performed on semitransparent ultrathin Cu(In,Ga)Se2 (CIGSe) solar cells on transparent conductive oxide, including nanostructures. The measurements are further extended by angular‐resolved performance studies. The bifaciality of the samples is determined to be ≈80% in current and ≈65% in power, and enables the calculation of an equivalent irradiance for solar cell testing under >1 sun front illumination only. The results are compared to bifacial operation, i.e., simultaneous front and rear irradiance, and to the summation of individual front and rear performance measurements up to 1 sun. It is revealed that highly similar results can be obtained for these approaches and that the integration of nanostructures supports device stabilization. Particularly, the higher (75 nm) SiO2 nanomeshes can enable performance enhancement. Furthermore, the angular‐dependent behavior follows the expected trend of reduced illumination intensity according to the cosine of the incident angle. In these findings, the suitability of semitransparent ultrathin CIGSe solar cells for bifacial operation and the benefit of integrated nanostructures is confirmed.

Wave resonances and the time-dependent capillary gravity wave motion

The interconnection of time and frequency domains for capillary gravity wave motion in the presence of current is discussed in this article. The general time-dependent problem is solved using Green’s function technique, and the asymptotic solution is derived using the method of stationary phase for large time and space. Also, the frequency domain solution is derived as a special case using the Cauchy Residue theorem. Different types of wave resonances like Trapping, Blocking and Bragg resonances are discussed. The existence of the trapped mode below the cutoff frequency is justified theoretically, and numerical results are obtained using the multipole expansion method. The blocking and Bragg resonances are analyzed above the cutoff frequency. It is found that in the presence of current, when the ripple wavenumber of the bottom undulation equals twice the cosine angle of incidence of wave times the wavenumber of the wave, Bragg resonance occurs. It is found that three propagating modes exist in the case of wave blocking, and the trapped modes exist only for the first propagating mode. Furthermore, because of the negative group velocity inside the blocking zone, the Bragg reflection increases while decreasing outside. The effect of current on the wave energy propagation in the form of group velocity is analyzed and the same is verified in the case of time-dependent problem.

Terminal velocity and drag coefficient of a smooth steel sphere moving in the water-filled vertical and inclined glass pipe (Newton regime)

This paper aimed to determine new data on terminal velocities and drag coefficients of single spheres moving inside a vertical and inclined glass pipe filled with water using the Particle Image Shadowgraph technique in the range of Reynolds numbers from 1420 to 12,740. The inclination angle α of the pipe varied from 0° to 30° relative to the vertical position. In the experiment, smooth steel spheres with diameters ranging from 3 to 9.5 mm were used, and the pipe had a fixed inner diameter of 40 mm. For verification, the experimental results of the drag coefficients were compared with known data from other authors for a free-settling sphere and a sphere rolling down a pipe wall or plane. Finally, the paper presents a new regression model describing the relationship between the sphere drag coefficient and Reynolds number when the cosine of the pipe inclination angle is varied.

Hangout Places Recommendation System Using Content-Based Filtering and Cosine Similarity Methods

Coffee shops are becoming the new normal for friends and coworkers to hang out. Selecting the ideal location to hang out can be exceedingly difficult. There are too many choices, and it can be difficult to know where to begin. Based on this problem, a web application that responds to the growing need for an easy method of finding local hangouts is named Nongkies. With a focus on social interaction and exploration, this platform uses a recommender system to find cafes, restaurants, and entertainment venues easily. Key features include location-based search, category, and details places. Extensive testing has confirmed the reliability of Nongkies, offering user-friendly and accurate search results. This system is a website app that suggests places to users based on their preferences. This application was developed using the cosine similarity method, which is a systematic approach that uses a similar method based on cosine angles. Content that is less alike gets lower rankings, while more similar content gets the highest rankings in recommendations. Moreover, this app helps users find local hangouts and directions to those locations, especially university students, and the selection of places to socialize has a significant effect on students' learning experiences.

Hyperspectral and Weather Resistant Biomimetic Leaf Enabled by Interlayer Confinement

AbstractMimicking the characteristics and achieving specific functions of biological systems is stirring but challenging. Generally, pigments in the commercial coating can only achieve a similarity in chromaticity, while cannot obtain a similarity in the solar reflective spectrum whose difficulty resides in simulating spectral characteristics simultaneously. Unfortunately, traditional organic pigments show poor weather and heat resistance. Herein, with the little difference in the color difference (ΔEab*), the high spectral similarity, as well as adjustable green peak and similar red edge slope compared with the common plants (pagoda tree leaf, etc.) in 400–2500 nm, is also attained. It is achieved by the interlayer confined organic pigment in Mg/Al‐layered double hydroxide (Mg/Al‐LDH) layers. The corresponding biomimetic leaf displays high hyperspectral performance with a spectral angle cosine of 0.9922 and heat resistance at 120 °C. The longer weather resistance than that of mechanical mixing is also demonstrated. The intercalated chromophores of sodium copper chlorophyllin in the Mg/Al‐LDH and the interlayer confinement of Mg/Al‐LDH contribute to the excellent performance. This work provides a green pigment and a biomimetic leaf requiring the same chromaticity and spectrum as green plants, filling the long‐term use demand gap for heat and weather‐resistant biomimetic vegetation.

Constructing a long-term global dataset of direct and diffuse radiation (10 km, 3 h, 1983–2018) separating from the satellite-based estimates of global radiation

In addition to global radiation (Rg), direct radiation (Rdir) and diffuse radiation (Rdif) are important fundamental data urgently needed in scientific and industrial fields. However, compared with Rg, Rdir and Rdif have received little attention in the past, either in observations or in satellite retrievals, mainly due to the high cost of their observations and the difficulty of retrieving them effectively from satellites. In this study, a long-term global gridded dataset of Rdir and Rdif was constructed by separating from a high-precision satellite-based product of Rg using the Light Gradient Boosting Machine (LightGBM) model, trained with in-situ observations measured at the Baseline Surface Radiation Network (BSRN). The inputs to construct the dataset are the four variables of Rg, the cloud transmittance for Rg, the ratio of Rdif to Rg under clear sky condition (call the clear diffuse ratio), and the cosine of the solar zenith angle. The developed dataset was validated against in-situ observations and compared with other satellite-based products. Evaluations against the BSRN observations indicated that our proposed method has good generality and outperforms the machine learning-based direct estimation method of Hao et al. (2020). Independent validations were further performed against the observations measured at 17 China Meteorological Administration (CMA) radiation stations and the estimation based on sunshine duration observations at >2400 CMA routine meteorological stations, respectively. It was found that the accuracies of our estimates for both Rdir and Rdif were improved when upscaled to ≥ 30 km. Comparisons with three other satellite-based products indicate that our developed dataset of both Rdir and Rdif was generally more accurate than the global products of the Earth's Radiant Energy System (CERES) and Hao et al. (2020) based on the Deep Space Climate Observatory/Earth Polychromatic Imaging Camera (EPIC) (DSCOVER/EPIC) satellite, and the regional gridded product (JIEA) of Jiang et al. (2020a). The dataset developed in this study will contribute to ecological research and solar engineering applications.

CAS3D: 3D quantitative morphometry on Second Harmonic Generation image volumes from single skeletal muscle fibers

The CAS3D image processing method intuitively applies a combination of Fourier space and real space 3D analysis algorithms to volumetric images of single skeletal muscle fiber Myosin II Second Harmonic Generation (SHG) XYZ image data. Our developed tool automatically quantifies the myofibrillar orientation in muscle samples by determining the cosine angle sum of intensity gradients in 3D (CAS3D) while determining the mean sarcomere length (SL) and sample orientation. The expected CAS3D values could be reproduced from ideal artificial data sets. Applied random noise in artificial images lowers the detected CAS3D value, and for noise levels below 20%, the correlation can be approximated by a linear function with a slope of −0.006 CAS3D/noise%. The deviations in SL and orientation detection were determined on ideal and noisy artificial data sets and were statistically indistinguishable from 0 (null hypothesis t-test P > 0.1). The software was applied to a previously published data set of single skeletal muscle fiber volumetric SHG image data from a rat intensive care unit (ICU) model of ventilator-induced diaphragm dysfunction (VIDD) with treatment regimens involving the small anti-inflammatory molecules BGP-15, vamorolone, or prednisolone. Our method reliably reproduced the results of the previous work and improved the standard deviation of the cosine angle sum detection in all sample groups from a mean of 0.03 to 0.008. This improvement is achieved by applying analysis algorithms to the whole volumetric images in 3D in contrast to the previously common method of slice-wise XY analysis.

Research on Path Planning Algorithm of Driverless Ferry Vehicles Combining Improved A* and DWA.

In view of the fact that the global planning algorithm cannot avoid unknown dynamic and static obstacles and the local planning algorithm easily falls into local optimization in large-scale environments, an improved path planning algorithm based on the integration of A* and DWA is proposed and applied to driverless ferry vehicles. Aiming at the traditional A* algorithm, the vector angle cosine value is introduced to improve the heuristic function to enhance the search direction; the search neighborhood is expanded and optimized to improve the search efficiency; aiming at the problem that there are many turning points in the A* algorithm, a cubic quasi-uniform B-spline curve is used to smooth the path. At the same time, fuzzy control theory is introduced to improve the traditional DWA so that the weight coefficient of the evaluation function can be dynamically adjusted in different environments, effectively avoiding the problem of a local optimal solution. Through the fusion of the improved DWA and the improved A* algorithm, the key nodes in global planning are used as sub-target punctuation to guide the DWA for local planning, so as to ensure that the ferry vehicle avoids obstacles in real time. Simulation results show that the fusion algorithm can avoid unknown dynamic and static obstacles efficiently and in real time on the basis of obtaining the global optimal path. In different environment maps, the effectiveness and adaptability of the fusion algorithm are verified.

Integrating Ray Tracing with Single-Objective Optimization in Heliostat Field Design

Tower solar thermal power generation is a new type of low-carbon and environmentally friendly clean energy technology. Through continuous optimization of the optical efficiency of mirror field and other key technologies, the energy utilization efficiency and economic benefits of solar thermal power stations can be improved, and contribute to the sustainable development of clean energy. This paper establishes a geometric model based on the light tracing method to solve the daily average, average annual optical efficiency, thermal output power, and average optical efficiency of the heliostatic field. The cosine efficiency is the cosine of the incident light and the normal angle, which is the cosine of the incidence angle; the atmospheric transmission is only related to the distance between the mirror center and the collector center; the mirror reflection constant is 0.92. The shadow occlusion efficiency and the truncation efficiency of the collector are the difficulties in the process of calculating the optical efficiency: for the calculation of the shadow occlusion efficiency, the Monte Carlo light tracing method is adopted. Based on the energy density of the helioscope, the occlusion efficiency of the shadow can be expressed as the ratio between the amount of the outgoing light to the total generated amount; for the calculation of the collector truncation efficiency, it links the reflected light with the surface equation of the collector. According to the joint results, if there is a solution, it means that the reflected light can be reflected in the collector, and the collector truncation efficiency can represent the ratio of the number of lights reflected in the collector to the number of unblocked lights in all the reflected lines. Finally, the average annual optical efficiency and output power parameters are respectively: 0.6093, 0.7431, 0.9283, 0.9828, 35. 4430MW, 0.5642kW/m². Results for the remaining months are shown in the main text.

An application of the supremum cosine angle between multiplication invariant spaces in $$\varvec{L^2(X; \mathcal H)}$$

An application of the supremum cosine angle between multiplication invariant spaces in $$\varvec{L^2(X; \mathcal H)}$$

Carbon Emission Right Price Prediction based on IOWHA Operator Vector Angle Cosine Combination Deep Learning

The relentless exacerbation of the greenhouse effect poses a significant challenge to the progress and sustainability of human civilization. Carbon emission rights serve as a pivotal gauge of the carbon trading market's dynamics. Examining the impact of carbon emission rights prices can shed light on how governments indirectly influence these prices through mechanisms such as carbon emission quotas and permits. This study focuses on analyzing the transaction prices of carbon emission rights quotas within the Guangzhou carbon trading market spanning from January 2015 to March 2023. Leveraging a selection of 17 variables across the realms of energy prices, macroeconomics, financial markets, and ecological environment, and drawing insights from the predictive outcomes of three distinct sub-models—namely Ridge Regression, Random Forest Regression, and Long Short-Term Memory neural network (LSTM)—a novel IOWHA operator vector angle cosine combination model is devised. The findings underscore that this combined model harnesses the predictive strengths of each sub-model, effectively curbing prediction discrepancies, and enhancing overall accuracy. The integration of these methodologies represents an optimal fusion for predictive modeling.

Shear wave anisotropy response characteristics of laminated shale and its correction methods

Laminated shale exhibits strong anisotropic characteristics in horizontal wells, significantly affecting the application of shear wave travel time data. Using equivalent medium theory and the elastic wave equation, we constructed a physical model for laminated shale, simulating the impact of lamination angle and lamination density on shear wave velocity and shear wave anisotropy coefficient. We established the relationship between the shear wave anisotropy coefficient and the cosine of the lamination angle. The simulation results indicate that shear wave velocity decreases with an increase in lamination angle and density, while the shear wave anisotropy coefficient gradually decreases with an increase in lamination angle and initially increases and then decreases with an increase in lamination density. Moreover, it exhibits a power exponential relationship with the cosine of the lamination angle. After correction, the minimum horizontal principal stress and fracture pressure calculated from shear wave data show an average relative error reduction of 6.72% and 7.77%, respectively, compared to measured data. This demonstrates that the correction method effectively eliminates the impact of laminated shale anisotropy on shear waves.

Novel criteria for silicone rubber insulators condition monitoring based on leakage current analysis: Considering asymmetric aging and pollution

Insulators' flashover due to pollution is the biggest challenge of power systems. This phenomenon will become more intense with the aging of the insulator. Precise and prompt determination of the severity of pollution and the insulator status in terms of aging is essential for preventing pollution flashovers. Therefor monitoring insulator leakage current is essential for preventing the pollution flashover phenomenon. This article proposes innovative criteria based on the insulator's leakage current analysis for the classification of aging and pollution severity. The leakage current signal of the virgin, fully aged, and asymmetric aged insulators have been examined under different pollution conditions. Based on the experimental results analysis, two new criteria have been proposed for assessing the silicon rubber insulator condition which have resulted from the first-order harmonic of leakage current (It1), the third and fifth-order harmonics ratio of leakage current (It3/5), and the cosine of first-order harmonic phase angle (PI). Analyzing the proposed criteria demonstrates that two proposed criteria have a strong correlation to aging and pollution, respectively. These two new criteria can be implemented to identify the early signs of pollution and aging of insulators. The ability of proposed criteria has been established based on random forest, support vector machine, decision tree algorithm, multi-layer perceptron, and decision-making level fusion in Python language. The obtained criteria based on experimental data in different conditions have been employed for classifier training which can be applied in industrial settings without the need for laborious data labeling, ensuring fast and accurate outcomes.

GNSS/5G Joint Position Based on Weighted Robust Iterative Kalman Filter

The Global Navigation Satellite System (GNSS) is widely used for its high accuracy, wide coverage, and strong real-time performance. However, limited by the navigation signal mechanism, satellite signals in urban canyons, bridges, tunnels, and other environments are seriously affected by non-line-of-sight and multipath effects, which greatly reduce positioning accuracy and positioning continuity. In order to meet the positioning requirements of human and vehicle navigation in complex environments, it was necessary to carry out this research on the integration of multiple signal sources. The Fifth Generation (5G) signal possesses key attributes, such as low latency, high bandwidth, and substantial capacity. Simultaneously, 5G Base Stations (BSs), serving as a fundamental mobile communication infrastructure, extend their coverage into areas traditionally challenging for GNSS technology, including indoor environments, tunnels, and urban canyons. Based on the actual needs, this paper proposes a system algorithm based on 5G and GNSS joint positioning, aiming at the situation that the User Equipment (UE) only establishes the connection with the 5G base station with the strongest signal. Considering the inherent nonlinear problem of user position and angle measurements in 5G observation, an angle cosine solution is proposed. Furthermore, enhancements to the Sage–Husa Adaptive Kalman Filter (SHAKF) algorithm are introduced to tackle issues related to observation weight distribution and adaptive updates of observation noise in multi-system joint positioning, particularly when there is a lack of prior information. This paper also introduces dual gross error detection adaptive correction of the forgetting factor based on innovation in the iterative Kalman filter to enhance accuracy and robustness. Finally, a series of simulation experiments and semi-physical experiments were conducted. The numerical results show that compared with the traditional method, the angle cosine method reduces the average number of iterations from 9.17 to 3 with higher accuracy, which greatly improves the efficiency of the algorithm. Meanwhile, compared with the standard Extended Kalman Filter (EKF), the proposed algorithm improved 48.66%, 35.17%, and 38.23% at 1σ/2σ/3σ, respectively.

Increasing the Adhesion of Bitumen to the Surface of Mineral Fillers through Modification with a Recycled Polymer and Surfactant Obtained from Oil Refining Waste.

The purpose of this study was to optimize the processes of wetting fillers by varying the content of such additives as a surfactant and polymer in bitumen-mineral compositions in order to achieve optimal performance. The cosine of the contact angle was used as a criterion for assessing the adhesion of the bitumen binder to the surface of crushed stone. The effect of the additives' concentration on surface tension and adhesive efficiency in binary and ternary bitumen compositions was studied. The following chemicals were used as additives: the original product AS-1, industrial additive AMDOR-10, and used sealant AG-4I, a product based on polyisobutylene and petroleum oils. AS-1 was obtained from the oil refining waste in the laboratory of M. Kozybayev North Kazakhstan University. The ternary "bitumen-AG-4I-AS-1" composition provided a maximum decrease in the contact angle by 15.96° (gray crushed stone) and by 14.06° (red crushed stone) relative to original bitumen, providing better wettability of the mineral filler particles with the bitumen, and as a result, maximum adhesion between the bitumen and crushed stone. The optimal performance of the bitumen-mineral composition was recorded with the joint presence of additives in the bitumen: AS-1 at a level of 1.0 g/dm3 and AG-4I at a level of 1.0 g/dm3.

Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time

ABSTRACT With the increasing frequency of extreme events, daily gross primary productivity (GPP) is necessary to be accurately assessed to determine when and how much it is affected. Fluctuating environmental conditions contribute to diverse diurnal photosynthetic patterns influenced by changing atmospheric factors, including solar radiation, CO2 concentrations, and leaf temperature. This complexity underscores the challenge of accurately estimating daily GPP. We quantitatively assessed three temporal upscaling approaches – cosine of the solar zenith angle, extraterrestrial solar irradiance, and photosynthetic active radiation(PAR) – under varying sky conditions. Additionally, we introduced a novel correction method for universal temporal upscaling ratios. Instantaneous GPP values from the FLUXNET2015 dataset, acquired around the MODIS overpassing time, were utilized. The upscaled daily GPP exhibited minimal deviation from the half-hourly GPPs collected between 11 am and 1 pm, with increased discrepancies for GPPs later in the afternoon. The PAR-based approach demonstrated superior accuracy in the afternoon, effectively capturing incoming radiation changes due to clouds. Instant environmental variables-GPP relationships were weak under clear skies but exhibited moderate-to-high positive correlations under cloudy conditions. Analyzing the impact of the diffuse ratio of incoming photosynthetic active radiation on instantaneous GPP revealed limited enhancement at short time scales. On a daily scale, all three temporal upscaling approaches, under different ranges of clearness index, consistently underestimated daily GPP. We proposed a novel correction method, normalizing the difference between maximum and minimum air temperature in a day, notably reduced errors by approximately 10.69 and 21.07 gC m−2 d−1 for cosine of the solar zenith angle and extraterrestrial solar irradiance-based temporal upscaling approaches. We recommend adopting the corrected temporal upscaling factor globally due to its simplicity and improved accuracy.

Neural Network Parameterization of Subgrid‐Scale Physics From a Realistic Geography Global Storm‐Resolving Simulation

AbstractParameterization of subgrid‐scale processes is a major source of uncertainty in global atmospheric model simulations. Global storm‐resolving simulations use a finer grid (less than 5 km) to reduce this uncertainty by explicitly resolving deep convection and details of orography. This study uses machine learning to replace the physical parameterizations of heating and moistening rates, but not wind tendencies, in a coarse‐grid (200 km) global atmosphere model, using training data obtained by spatially coarse‐graining a 40‐day realistic geography global storm‐resolving simulation. The training targets are the three‐dimensional fields of effective heating and moistening rates, including the effect of grid‐scale motions that are resolved but imperfectly simulated by the coarse model. A neural network is trained to predict the time‐dependent heating and moistening rates in each grid column using the coarse‐grained temperature, specific humidity, surface turbulent heat fluxes, cosine of solar zenith angle, land‐sea mask and surface geopotential of that grid column as inputs. The coefficient of determination R2 for offline prediction ranges from 0.4 to 0.8 at most vertical levels and latitudes. Online, we achieve stable 35‐day simulations, with metrics of skill such as the time‐mean pattern of near‐surface temperature and precipitation comparable or slightly better than a baseline simulation with conventional physical parameterizations. However, the structure of tropical circulation and relative humidity in the upper troposphere are unrealistic. Overall, this study shows potential for the replacement of human‐designed parameterizations with data‐driven ones in a realistic setting.

A Conflict Evidence Fusion Method Based on Bray–Curtis Dissimilarity and the Belief Entropy

The D-S evidence theory is extensively applied to manage uncertain information. However, the theory encounters challenges related to conflicts during the fusion process, impeding the precise identification of multi-subset focal elements. This paper introduces a novel method for conflicting evidence fusion that incorporates the Bray–Curtis dissimilarity, cosine distance of the included angle, and belief entropy. The method comprehensively evaluates three aspects—evidence similarity, evidence distance, and the amount of information—while considering factors like the credibility and uncertainty of evidence. Initially, the evidence undergoes conversion into single-subset focal element evidence through the improved Pignistic probability function. Subsequently, the credibility between pieces of evidence is established using the Bray–Curtis dissimilarity and angle cosine distance, while the uncertainty of the evidence is computed using belief entropy. The weighted correction coefficient of the evidence is determined by integrating the credibility and uncertainty of the evidence. Subsequently, the corrected evidence is fused using the D-S evidence theory to derive the final judgment. An analysis of two sets of arithmetic examples, considering both single-subset and multi-subset focal elements, demonstrates the faster convergence and enhanced accuracy and reliability of the proposed method in comparison to existing approaches.

Credit Risk Assessment of Listed Companies Based on Vector Angle Cosine

A study is conducted on the credit risk assessment model of listed companies in China. Firstly, factor analysis is used to construct an indicator system from five dimensions: debt paying ability, development ability, operating ability, profitability, and cash flow. Then, the cosine method of vector angle is used to replace the subjective expert scoring method and assign weights to the indicators. Finally, based on the scoring model, the scores of 25 listed companies are calculated and their credit risk is evaluated.