Due to the large amount of data involved in the three-dimensional (3D) LiDAR point clouds, point cloud compression (PCC) becomes indispensable to many real-time applications. In autonomous driving of connected vehicle...
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Due to the large amount of data involved in the three-dimensional (3D) LiDAR point clouds, point cloud compression (PCC) becomes indispensable to many real-time applications. In autonomous driving of connected vehicles for example, point clouds are constantly acquired along the time and subjected to be compressed. Among the existing PCC methods, very few of them have effectively removed the temporal redundancy inherited in the point clouds. To address this issue, a novel lossy LiDAR PCC system is proposed in this paper, which consists of the inter-frame coding and the intra-frame coding. For the former, a deep-learning approach is proposed to conduct bi-directional frame prediction using an asymmetric residual module and 3D space-time convolutions;the proposed network is called the bi-directional prediction network (BPNet). For the latter, a novel range-adaptive floating-point coding (RAFC) algorithm is proposed for encoding the reference frames and the B-frame prediction residuals in the 32-bit floating-point precision. Since the pixel-value distribution of these two types of data are quite different, various encoding modes are designed for providing adaptive selection. Extensive simulation experiments have been conducted using multiple point cloud datasets, and the results clearly show that our proposed PCC system consistently outperforms the state-of-the-art MPEG G-PCC in terms of data fidelity and localization, while delivering real-time performance.
A new chromosome encoding method, named fuzzy coding, is proposed for representing real number parameters in a genetic algorithm. Fuzzy coding provides the value of a parameter on the basis of the optimum number of se...
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A new chromosome encoding method, named fuzzy coding, is proposed for representing real number parameters in a genetic algorithm. Fuzzy coding provides the value of a parameter on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree of membership. Thus, it represents the knowledge associated with each parameter and is an indirect method of encoding compared with alternatives, where the parameters are directly represented in the encoding. Fuzzy coding is described and compared with conventional binary coding, gray coding, and floating-point coding. Two test examples, along with neural identification of a nonlinear pH process from experimental data, are studied. It is shown that fuzzy coding is better than the conventional methods and is effective for parameter optimization in problems where the search space is complicated.
The identification methods of industrial process are discussed The applied MATLAB program of least squares method is given and used to identify pulse transfer function. A kind of improved genetic algorithm is introduc...
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ISBN:
(纸本)0780385608
The identification methods of industrial process are discussed The applied MATLAB program of least squares method is given and used to identify pulse transfer function. A kind of improved genetic algorithm is introduced to identify the transfer function and parameters of nonlinear dynamic model of thermal process. In the algorithm, floating-point coding, rank-based selection, elitist reservation and grouping method are used, the premature convergence is restrained, the global and local searching ability is improved With the genetic algorithm, the transfer function of topical thermal process can be identified accurately. The parameters of nonlinear model can be modified according to operating data of power plant, no matter what kind of input signal is used, such as step signal, random operating signal.
It is very difficult to find the initial state of the backward analysis in a traditional simulative calculation of bridge construction because of the bearing peculiarity of the Concrete Filled of Steel Tubular(CFST) a...
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It is very difficult to find the initial state of the backward analysis in a traditional simulative calculation of bridge construction because of the bearing peculiarity of the Concrete Filled of Steel Tubular(CFST) arch *** this paper,the genetic algorithm had to search for the optimized closure state in the arch-rib construction,which can be taken as the initial state for the backward *** to the detailed analysis,the objective function was determined, which included the adjustment increment of cable length as the variable *** the objective function could only be obtained by the structural simulation calculation,which makes the searching more *** a method using floating-point genetic algorithm was adopted and the genetic operation was adjusted to improve the precision and speed of the genetic *** the optimized closure state in arch-rib construction was obtained with an improved genetic algorithm in an example *** was shown that the results of the method could be used as the initial state for the backward analysis.
It is very difficult to find out the initial state of the backward analysis in traditional simulative calculation of bridge construction because of the bearing peculiarity of concrete filled of steel tubular arch brid...
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It is very difficult to find out the initial state of the backward analysis in traditional simulative calculation of bridge construction because of the bearing peculiarity of concrete filled of steel tubular arch bridge. In this paper, the genetic algorithm is introduced to search the optimized closure state in archrib construction, which can be taken as the initial state of backward analysis. According to the detailed analysis, the target function is determined, which takes adjustment increment of cable length as a variable parameter. But the target function can be obtained only through structural simulative calculation, which makes the searching more complicated. So the floating-point genetic algorithm is adopted and the genetic operation is ameliorated to improve precision and speed of the genetic search. Finally the optimized closure state in arch-rib construction is obtained using the improved genetic algorithm in a calculation example. It proves that the results can be used as the initial state for the backward analysis.
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