An optimized deep neural network-based financial statement fraud detection in text mining

Yadav, Ajit Kr. Singh; Sora, Marpe

doi:10.17993/3cemp.2021.100448.77-105

Cited by 26 publications

(20 citation statements)

References 24 publications

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“…This acceleration time history is converted to an https://doi.org/10.17993/3ctic.2023.121. [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] elastic spectrum response using PRISM software to get the spectral (acceleration, velocity, and displacement) as in Fig. 2.…”

Section: Methods Of Response Spectrummentioning

confidence: 99%

“…Alternating electrical conductivity (a.c.) in insulating materials is determined by power lost as a result of applying an alternating electric field, which appears as heat and rotates dipoles in their positions or causes charges to vibrate by changing the direction of the alternating electric field. For this reason, the amount of power lost determines the frequency of the applied field [36]. By increasing the weight ratios of the reinforcement with nano-oxides (MgO, GO), it is noted that the alternating electrical conductivity is high compared to the alternating electrical conductivity of the pure PVA membrane, which is few, as well as the formation of a continuous network in the form of agglomerates when the weight ratio of nano-oxides is increased, which it leads to the formation of a continuous path inside the hybrid nanocomposite films material as the weight ratio increases, Because of the formation of a continuous conductive path, this leads to an increase in the AC electrical conductivity, and its value is determined by the effect of polarization and electron movement in the substrate [32].…”

Section: Electrical Conductivity (σAc)mentioning

confidence: 99%

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Untitled

2023

3C TIC

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In this work, a pure (PVA) polymer film reinforced with magnesium oxide, graphene oxide poly (o-phenylene diamine) (GO-MgO-PoPDA) was created utilizing the solution casting process in various weight ratios (0, 2, 4, 6, 8, 10 wt%). It was investigated how varied weight ratios of the nanoparticles magnesium oxide (MgO) and graphene oxide (GO) affected the Dielectric Properties of nano composite films. FTIR, SEM,X-RAY were used to characterized the nanocomposite. The results of the dielectric properties showed that the values of the alternating electrical conductivity of the prepared films increase when adding (GO-MgO-PoPDA) nanoparticles and with the increase of the frequency of the applied electric field and the increase of the particle content, while the values of the dielectric constant increase with the increase of each of the content of (GO-MgO-PoPDA) nanoparticles, but it decreases with increasing frequency. Whereas, the dielectric loss coefficient of the prepared films decreases when nanoparticles are added and with increasing frequency.

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Section: Methods Of Response Spectrummentioning

confidence: 99%

Section: Electrical Conductivity (σAc)mentioning

confidence: 99%

Untitled

2023

3C TIC

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“…The air and heat exchanger surface temperature difference control method uses the difference between the heat exchanger outlet temperature and the ambient temperature for defrost control (Nilpueng et al, 2019;Su et al, 2021;Yi, 2021). It can be said that assuming that the ambient temperature remains unchanged and the heat exchanger surface does not reach the condition of frost, the heat exchanger surface temperature is basically unchanged at this time, so the difference with the ambient temperature is unchanged, but when the heat exchanger surface reaches the condition of frost, that is, when it starts to frost, the difference between the two will show significant changes (Juárez et al, 2021;Singh and y Sora, 2021). So, you only need to determine the appropriate temperature difference value; it is good to determine whether the outdoor heat exchanger surface has been frosted and a certain defrost time can be, but the defrost method is only suitable for specific situations because different systems need to determine other temperature difference values and different defrost time, and the heat pump air conditioning system is more sensitive to changes in load, such as changes in ambient temperature will cause excess defrost action.…”

Section: Electric Vehicle Heat Pump Defrost System Controlmentioning

confidence: 99%

Intelligent control system for the electric vehicle heat pump air conditioner based on machine learning

Ze-hua

2023

Front. Energy Res.

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In order to break through the existing battery technology of electric vehicles, this paper proposes to use heat pump air conditioning instead of the original PTC heating system potential. First, the advantages and disadvantages of different heat pump models for new energy vehicles are analyzed and compared. Second, a fuzzy inference system is constructed based on the machine learning model to observe the temperature of the passenger compartment using the temperature sensor inside the tram and to determine the need for the air conditioning system to be turned on in the heating/cooling mode by comparing it with the set temperature. Finally, the results show that the machine learning algorithm is able to monitor and adaptively adjust the interior temperature to further enhance the adaptability of the system with low volatility and high accuracy. The proposed research study can lay the foundation for further optimizing the design of heat pump air conditioners for electric vehicles.

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“…We suggest applying optimization techniques, especially a deterministic approach [18], to reduce the size and complexity of the optimization issue [19]. Many algorithms have been studied [20], but the well-known Sequential Quadratic Programming (SQP) algorithm has ultimately been chosen as the current approach for handling challenging nonlinear and restricted programming issues [21].…”

Section: Tolerances Impact On the Designmentioning

confidence: 99%

Components’ Tolerance Impact on the Design of a Real Case of One MW PV Substation

Ayed

Chakroun

Derbel

et al. 2023

Discrete Dynamics in Nature and Society

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In this article, a real case of a one MW PV substation design problem is described. The impact of the tolerances of power components (mainly inductors and capacitors) on the design is highlighted through two studies using two different control strategies that are selective harmonic elimination (SHE) and selective harmonic modulation (SHM). The obtained results show that the components’ tolerances have a significant effect on the design, especially for the SHE strategy. While the design using SHM control shows a weak sensitivity to the components’ tolerance. In this study, an upgrade of the most sensitive control strategy is proposed in order to improve its sensitivity against components’ tolerance. The results show that the strategy upgrading leads not only to improving the sensitivity but also to generating better power quality.

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An optimized deep neural network-based financial statement fraud detection in text mining

Cited by 26 publications

References 24 publications

Untitled

Untitled

Intelligent control system for the electric vehicle heat pump air conditioner based on machine learning

Components’ Tolerance Impact on the Design of a Real Case of One MW PV Substation

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