Cultivated land quality (CLQ) is associated with national food security, benign economic development, social harmony, and stability. The scientific evaluation of CLQ provides the basis for achieving the "trinity ...
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Cultivated land quality (CLQ) is associated with national food security, benign economic development, social harmony, and stability. The scientific evaluation of CLQ provides the basis for achieving the "trinity " protection of cultivated land quantity, and quality, as well as ecology. However, the current research on CLQ evaluation has some limitations, mainly the poor consideration of evaluation indicators, time-consuming and labor-intensive data acquisition, and low precision of evaluation at the regional scale. Therefore, this study introduced multisource data to evaluate CLQ and proposed a new method for CLQ evaluation (natural grade evaluation, utilization grade evaluation, and economic grade evaluation), combining multisource data and the recurrent neural network (rnn) algorithm. Initially, optimal indicators were determined by correlation analysis and generalized linear regression coefficient methods based on factors related to CLQ acquired from multisource data. Then, CLQ evaluation models were constructed with the rnn algorithm on the basis of the aforementioned optimal indicators. Finally, the models were adopted to map CLQ. The present study was carried out in Guangzhou City, Guangdong Province, China. According to the results: (1) CLQ showed close relationship to pH, effective soil layer thickness (EST), chemical fertilizer application rate (CHFE), organic matter content (OMC), annual accumulated temperature (TEMA), 5-15 cm soil depth soil cation exchange capacity (CEC515), 0-5 cm soil depth soil cation exchange capacity (CEC05), 5-15 cm soil depth soil organic carbon content (SOC515), 0-5 cm soil depth soil organic carbon content (SOC05), field slope (FS), groundwater level (GWL), and terrain slope (TS). (2) All modeling accuracies (R2) were greater than 0.80 for the CLQ evaluation models constructed based on the rnn algorithm. The area and spatial distribution of each grade of CLQ evaluation were consistent with the actual situation. The best and the
Power analysis methods are commonly used for evaluating the security of cryptographic *** are characteristically low-cost and display a high success rate and the ability to obtain important device information, e.g., k...
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Power analysis methods are commonly used for evaluating the security of cryptographic *** are characteristically low-cost and display a high success rate and the ability to obtain important device information, e.g., keys. Given the current wide application of deep-learning technology, there is a growing tendency to incorporate power-analysis technology in *** study investigates non-profiled deep-learning-based power analysis. The labels used in this attack are uncertain,and the attack conditions required are greatly reduced. We choose the Recurrent neural network(rnn), multilayer perceptron, and convolutional neural network algorithms,which use the same network structure, to recover the keys for the SM4 software and DES hardware *** propose combining the rnn algorithm with power analysis, and validate the benefits experimentally. The experimental results show that they all successfully recover the correct key for the SM4 software implementation,although the rnn algorithm by itself achieves a better effect. This conclusion also applies to attacks on the DES hardware implementation but is limited to labels based on the bit model.
The major development of the Internet of Things (IoT) has improved wireless technology in general and multiple sectors. Hardware security representations are crucial in maintaining the trustworthiness, credibility, an...
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The major development of the Internet of Things (IoT) has improved wireless technology in general and multiple sectors. Hardware security representations are crucial in maintaining the trustworthiness, credibility, and credibility of integrated circuits (ICs) and digital equipment. Phlashing attacks have just been termed Permanent Denial of Service (PDoS) attacks since they behave similarly to a standard DoS attack but still have long-term implications. To prevent a PDoS intrusion that would block all Internet connectivity and related functionalities on a computer. A phlashing is a cyber-attack where an entity intentionally blocks another individual basis team from accessing internet resources also including network communication and financing. This article aims to provide an analysis of cyber-attack avoidance is identified and ceased by worldwide records across the last year to analyze data and developments in cyber-attacks. Attacks can be tracked better as the same form of attack is performed again by using a database containing the attack signatures. Our study revealed, by using the Recurrent Neural Network (rnn) algorithm, that our system could provide adequate detection efficiency while still correcting the detectors whenever an intruder is observed. (c) 2021 Elsevier B.V. All rights reserved.
In power quality (PQ) problems, the flexible AC transmission system (FACTS) devices have been developed the real power and reducing the PQ issues of the power system. Here the PQ analysis in photovoltaic (PV), wind tu...
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In power quality (PQ) problems, the flexible AC transmission system (FACTS) devices have been developed the real power and reducing the PQ issues of the power system. Here the PQ analysis in photovoltaic (PV), wind turbine (WT) system with grid integrated static switched filter compensator (SSFC) is controlled by adaptive technique. The adaptive technique works with the combined process of Cuttle fish algorithm (CFA) and recurrent neural network (rnn) algorithm. The proposed adaptive technique is controlling the irregular switching process of the shunt capacitor banks of a tuned arm filter in SSFC device. The novelty of the proposed technique is improved for energy efficiency and demand management in grid utilization process. Here a power injection model of SSFC is considered to control the real power flow control in terms of grid utilization. The switching process is controlled by balancing control signal generated with the help of pulse width modulation (PWM) process. To modulate the PWM is used by two regulators, which is based on a tri-loop real error managed combined weighted adjusted proportional integral derivative controller. The proposed SSFC system is designed and implemented in MATLAB/Simulink platforms and the performance is validated with some existing devices such as unified power flow controller and SSFC devices.
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