Energy finance is the product of the close combination of the energy industry and the financial industry, and the two affect each other. The energy crisis may lead to a financial crisis, and the financial crisis may a...
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Energy finance is the product of the close combination of the energy industry and the financial industry, and the two affect each other. The energy crisis may lead to a financial crisis, and the financial crisis may also lead to a energy crisis. Early risk warning for the energy financial crisis can effectively mitigate and reduce risks. This article used the gabp (Genetic algorithm Back Propagation) algorithm model to systematically analyze and predict the risks of energy financial crises. After establishing indicators for energy finance risk warning, this article collected relevant data from 150 energy companies and 210 financial companies, and compared them with the gabp algorithm model and manual analysis model. The error value of the model is determined by the numerical expansion in the positive and negative directions based on zero scale values. The closer the zero scale value is, the smaller the error;the farther it is from the zero scale value, the greater the error. The results show that the average accuracy of the gabp model for energy finance risk warning is 85.2%, and the minimum error value is -0.23. The average accuracy of using manual analysis models for energy finance risk warning is 75.8%, with a minimum error value of 1.89. The gabp algorithm has advantages in constructing energy finance risk warning models.
With the rapid development of the network era, the environment of computer network has become more complex, and the problems of network security are increasingly prominent. In this context, how to ensure the security ...
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With the rapid development of the network era, the environment of computer network has become more complex, and the problems of network security are increasingly prominent. In this context, how to ensure the security of data information and network system in the open network environment has become a problem need to be discussed and solved by relevant personnel. Therefore, in this paper, a research of the applications of gabp algorithm in the evaluation of computer network security is proposed according to the influence factors of computer network security and combined with the characteristics of gabp neural network algorithm. What's more, the construction scheme of computer network security defense system is fatherly discussed, aiming at improving the security of computer network system.
The actual bending shape of the rope-driven spine-like continuum mechanism deviates from the standard arc shape, and it is difficult to establish an accurate motion control model. In order to solve the problem of prec...
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ISBN:
(纸本)9798350366457;9798350366440
The actual bending shape of the rope-driven spine-like continuum mechanism deviates from the standard arc shape, and it is difficult to establish an accurate motion control model. In order to solve the problem of precise control of the end position of the two-stage flexible robot by fusing genetic algorithm and backpropagation neural network gabp, this paper studies the problem of precise control of the end position of the two-stage flexible robot. Through the joint simulation of Solidworks and ADAMS, the mapping database of the X, Y, and Z coordinates at the end of the flexible robot and the tensile length of the six soft axes were established, and the standard backpropagation BP neural network and gabp neural network models were trained by using the database, and the model parameters were optimized. Finally, the end motion trajectory of the robot was designed, and the BP and gabp neural network models were used to verify the position accuracy of the end of the flexible robot. The results show that both the standard BP and gabp models can realize the position control of the end of the flexible robot, and the position accuracy of the neural network model fused with genetic algorithm (maximum error: epsilon(x) = 0.73 mm, epsilon(y) = 0.78 mm, epsilon(z) = 1.82 mm) in controlling the motion of the flexible robot has been significantly improved compared with the standard BP neural network model (maximum error: epsilon(x) = 3.13 mm, epsilon(y) = 1.78 mm, epsilon(z) = 1.95 mm).
The internet has gradually penetrated into people's daily lives. However, with the popularization of the Internet, its negative impact has also followed. With the emergence of the Internet, behaviors such as hacke...
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High-precision and fault-tolerant six-dimensional force/torque sensor is one of the core components of intelligent robots for force feedback perception. This paper is aiming at the fault-tolerant measurement mechanism...
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High-precision and fault-tolerant six-dimensional force/torque sensor is one of the core components of intelligent robots for force feedback perception. This paper is aiming at the fault-tolerant measurement mechanism research on piezoelectric six-dimensional force/torque sensors with four-point support structure. Based on principle of leverage and deformation consistent, the fault-tolerant measurement mechanism of the pre-tightened four-point supported piezoelectric six-dimensional force/torque sensor is revealed. The mapping mathematical models of spatial six-dimensional force and four-fulcrum quartz crystal group detection signal for the sensor without signal fault and with signal fault are constructed respectively. The static calibration system of the sensor is built to realize the fault-tolerant static calibration experiment of the four-point supported piezoelectric six-dimensional force/torque sensor prototype under unidirectional loading without signal fault and with signal fault. In order to improve the measurement precision of six-dimensional force/torque sensor for robot, a decoupling method based on Genetic algorithm to optimize Back Propagation algorithm (gabp) for piezoelectric six-dimensional force/torque sensor is adopted to solve the nonlinear cross coupling problem of multiple-input and multiple-output. Through Maltlab software, the test data are analyzed and calculated, and the percentage coupling error matrix of the sensor is calculated. The percentage coupling error is different when the sensor is fault-free and the fault-free measurement model is different. When the sensor is fault-free, the linearity of the sensor is the best and the maximum coupling error is less than 1.5%. When the sensor has any branch fault, the overall performance of the sensor is relatively weakened and the maximum coupling error increases. When the sensor has two branch faults, the linearity of the sensor is the worst. It cannot satisfy the requirement of accurate measur
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