A feedforward-feedback control strategy based on artificial neural network for solar receivers

Wang, Wenqi; Sun, Qiuye; Guo, Jiaqi; Tao, Wen‐Quan

doi:10.1016/j.applthermaleng.2023.120069

Cited by 12 publications

(4 citation statements)

References 36 publications

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“…This observation provides the foundational framework for entry and exit assessments. Specifically, the coordinates of the pressure's center of gravity within each frame are discerned, and the entry or exit status is contingent upon the polarity (positive or negative) of its corresponding y-coordinate change.In a more generalized perspective, the center of gravity for an image spanning dimensions w by h can be mathematically determined as exemplified in Equation 1: The fundamental computational components of the BP neural network are neurons [17]. This network exhibits robust prowess in nonlinear mapping, a characteristic that forms the bedrock for employing the BP neural network methodology within this paper.…”

Section: Bp Neural Network Based Shoe Print Identification Modulementioning

confidence: 99%

People recognition with foot pressure based on neural network

Zhao

2024

Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023)

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To find the suspect in forensic cases, a unique feature of shoe prints can be used. It is effective to distinguish people with shape of shoes and gait features demonstrated by many studies. To address the limitations stemming from relying solely on a single feature, such as complex equipment requirements and susceptibility to interference, this study explores a people identification system that leverages a BP neural network while integrating both shape and plantar pressure features. With 3 different approaches of data processing compared, an accuracy of 89% with no noises and 74%with10% gaussian noise. The result demonstrated that the system is effectiveness on people identification.

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Section: Bp Neural Network Based Shoe Print Identification Modulementioning

confidence: 99%

People recognition with foot pressure based on neural network

Zhao

2024

Fourth International Conference on Computer Vision and Data Mining (ICCVDM 2023)

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“…DC-DC converters are needed to connect solar cells to electrical devices and to provide energy balance [10,11]. In order to increase efficiency and stability in energy systems, the design, analysis, and control of power circuits that provide transformation in the system are of great importance [12,13]. In order to optimize and control the DC-DC converter structures, the mathematical structure of the system should be analyzed and created [14,15].…”

Section: Introductionmentioning

confidence: 99%

PID Control of Hybrid DC-DC Converter System in Complex Load with Double Reference Time

Can,

Gülnahar

2024

Teh. glas. (Online)

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DC-DC converters are circuits that are widely used in energy distribution systems, in industry and technology applications, as well as in household appliances such as computers and televisions, and in uninterruptible power supplies used to feed all these systems. For the design and optimization of DC-DC converter circuits, it is important to create and analyze mathematical models according to the load it is connected to. Simple load structures and circuit structures have been examined and control units have been designed in studies carried out to date. In this study, while the DC-DC converter with a more complex load structure is discussed, mathematical analysis and PID control of DCDC converters with Buck-Boost feature are performed with the same modulation index in different time periods. In the results obtained, it is shown how to create the mathematical models of a system that provides DC-DC energy conversion with a complex load structure and how to formulate the PID control in a system with this complex load structure.

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“…The ANN that has stepped into the world in the mid-20th, is a computational scheme utilized to develop algorithms for modeling complex patterns [ 31 ]. The other effective technique to optimize the parameters and specify the best operating condition in the engineering processes is RSM [ [32] , [33] , [34] ] This scheme allows assessing the impacts of multiple parameters and their interactions on the examined responses [ [35] , [36] , [37] ].…”

Section: Introductionmentioning

confidence: 99%

Thermo-hydraulic performance optimization of a disk-shaped microchannel heat sink applying computational fluid dynamics, artificial neural network, and response surface methodology

Vaferi,

Vajdi,

Nekahi

et al. 2023

Heliyon

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A feedforward-feedback control strategy based on artificial neural network for solar receivers

Cited by 12 publications

References 36 publications

People recognition with foot pressure based on neural network

People recognition with foot pressure based on neural network

PID Control of Hybrid DC-DC Converter System in Complex Load with Double Reference Time

Thermo-hydraulic performance optimization of a disk-shaped microchannel heat sink applying computational fluid dynamics, artificial neural network, and response surface methodology

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