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In order to improve the power supply quality of sine wave inverter for small wind power system, a control method that combines BP neural network (BPNN) with genetic algorithm (GA) is proposed in this paper. The BPNN is optimized by means of the GA to avoid the BPNN falling into local optimum value, and the optimized BPNN can better control the power output of the designed sine wave inverter. Simulation...
With the expansion of monetary globalization and development of data innovation, budgetary information are being created and gathered at a remarkable pace. Therefore, there has been a basic requirement for robotized ways to deal with compelling and proficient use of huge measure of money related information to bolster organizations and people in key arranging and speculation basic leadership. Information...
This paper presents a way of combining BP (Back Propagation) neural network and an improved PSO (Particle Swarm Optimization) algorithm to predict the earthquake magnitude. It is known that the BP neural network and the normal PSO-BP neural network have some defeats, such as the slow convergence rate, easily falling into local minimum values. For improving the properties of PSO, some proposed the...
Considering the fuzziness and diversity of the capsule foreign matter defect in the image, the BP neural network is applied to discern the capsule foreign matter defect Firstly, the capsule image is separated into three parts by vertical Sobel operator, and every part of image is processed by median filter to clear the noise. Then the histogram features of all the three parts of the image, namely...
This paper proposed a visual servoing control scheme for positioning a robot manipulator. Similar to the behaviour of human, this scheme is divided into two steps: firstly a fuzzy logic-based visual servoing controller is used to guide the gripper into the neighbourhood of the object, and then one local neural network is applied to position the gripper in a desired pose. The whole control needs no...
This paper proposed a visual servoing control scheme for positioning a robot manipulator. Similar to the behaviour of human, this scheme is divided into two steps: firstly a fuzzy logic-based visual servoing controller is used to guide the gripper into the neighbourhood of the object, and then one local neural network is applied to position the gripper in a desired pose. The whole control needs no...
A new visual servoing control schemes is proposed for the robot arm movements, which is similar to the pick behavior of human. Firstly a visual servoing controller based on fuzzy logic is used to move the gripper into the neighborhood of the object. Then one local neural network uses image error to position and orientate the gripper exactly. The whole control, which needs no calibration of the robot...
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