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An important application field of swarm intelligence algorithms is fuzzy rule acquisition. However, their limitations are showed in two aspects. On one hand, it takes a long process to create fuzzy rules during the iterations; on the other, the swarm intelligence algorithms obtain local optimal solution at times. To overcome these disadvantages, a dynamic hybrid swarm intelligence approach is proposed...
The accurate positioning is the core technology of mobile robot. The paper proposes a visual odometry method based on trifocal tensor to get the high-precision positioning information of autonomous robot. Two-wheel car was used to simulate the mobile robot, where monocular camera was mounted on. We employed camera calibration algorithm to get intrinsic parameters, the IPM (Inverse Perspective Mapping)...
This paper presents a solution for the license plate recognition problem under low illumination on the basis of in-depth analysis of the characteristic of license plate images. In recent years, with the development of technologies such as optics, computers and pattern recognition, license plate recognition technology is improved constantly, but the accuracy of license plate recognition under low illumination...
An ultrahigh photocurrent (PC) signal which was about thousand times higher compared to the corresponding dark current was achieved in a two-dimensional (2D) multi-layer MoS2 field effect transistor (FET), owing to a gate-controlled MoS2/Ti/Au Schottky barrier (SB) modulation. The SBs can be enlarged for suppressing the electron drift along the channel in dark environment, and be reduced for the collection...
Carrier frequency synchronization is important in MIMO-OFDM systems. Any carrier frequency offset will cause a loss of subcarrier orthogonality which results in ICI and hence performance degrades severely. In this paper, a preamble structure for MIMO-OFDM systems is proposed. Based on the structure, the carrier frequency synchronization algorithm in burst data transmission for MIMO-OFDM systems is...
By the analyze of chaos for runoff series, combing the reconstruction phase space theory and BP neural network to develop the BP neural network model based reconstruction phase space, and forecast the runoff series mensal in Xiaoqing river hydrological station of Jinan, the result shows that the model has a very good forecast accuracy and value.
By the main component analysis, and maximum Lyapunov index method, this paper analyses chaotic character of ground water level time series. On this basis, combining the reconstruction phase space of chaos theory with BP neural network to set up a BP neural network model based on chaos theory. This paper forecasts ground water level of the Heihu Spring in Jinan by the model. The result shows that the...
Based on analysis of former matter element extension evaluating model, author points out the former model's limitation that the model can not be used when observed data are bigger than the section field value in evaluation of water quality. Combining synthesis weights with approach degree, a new matter element extension evaluating model based on synthesis weights and approach degree is established...
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