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In this paper, a novel nonlinear Radial Basis Function Neural Network (RBF-NN) ensemble model based on ν-Support Vector Machine (SVM) regression is presented for financial time series forecasting. In the process of ensemble modeling, the first stage the initial data set is divided into different training sets by used Bagging and Boosting technology. In the second stage, these training sets are input...
This paper proposes a fast target tracking method in which particle filter is improved using Gaussian kernel and evolutionary strategy. We use Gaussian kernel function to replace the Dirac kernel function, which can decrease the degeneracy problem of the traditional particle filter partly. To further improve the performance of particle filter, we introduce evolutionary strategy into the process of...
In this paper, we investigate the multistablility of almost periodic solutions of neural networks with a class of discontinuous activation functions. It shows that the n-neuron neural networks can have (r + 1)n (r ≥ 1) exponentially stable almost periodic solutions. As special cases, the multiperiodicity and multistability of neural networks with periodic or constant coefficients are derived respectively...
This paper designs a time-varying nonlinear switching manifold in an optimal fashion for a class of nonlinear systems by developing the successive approximation approach of differential equation into infinite-time horizon. Based on the reaching law approach, we obtain a reach the nonlinear sliding surface. The stability of the nonlinear sliding mode is analyzed. The convergence velocity of every state...
In engineering applications, Gaussian process (GP) regression method is a new statistical optimization approach, to which more and more attention is paid. It does not need pre-assuming a specified model and just requires a small amount of initial training samples. Based on the design of experiment (DOE), determining a reasonable statistical sample space is an important part for training the GP surrogate...
There are a large number of video data have to be processed and transmitted in resource-constrained wireless multimedia sensor networks (WMSN). One possible way of achieving maximum utilization of those resources is to apply an adaptive image coding scheme, which must consider the trade-off between energy consumption and image quality. The the major research challenges and objectives of image coding...
Different similarity measures for type-2 fuzzy sets have been proposed in the literature. However, there are not analytical formulas for them. In this paper, an extension of Jaccard's similarity measure for type-2 fuzzy sets is considered and the generalized formula in analytical form for the similarity measure of two interval fuzzy sets with Gaussian Primary membership function is derived.
Since the sole focus can't capture the high-quality image of multi-association plastic gear tooth profile's flaw detail on different end surface, these flaws couldn't be detected simultaneously. When it comes to the two images focused on different gear ends, the highly detailed image is required due to the large quantity and complex profile of gear teeth. In view of the subject above, some fusion...
Human experts frequently communicate to find a solution to a complicated problem or to confirm their thought about how to solve a problem. An expert system could be facilitated to consult with other same domain expert system in order to better handle a request, too. In this paper a distributed rule-based expert system is designed and implemented. The required protocol for the communication of the...
Based on granularity distribution of soil having fractal character, the fractal dimension of soil is studied by theory analysis and calculation. The structure character of soil is quantized by using fractal dimension, which build up a foundation for neural network considering soil structure in the process of prediction of frost heave. Topology structure of BP neural network is built, and L-M arithmetic...
We propose a fast adaptive learning algorithm for computing principal eigenvector of covariance matrix arisen in the field of signal processing, where the learning process has to be repeated in online manner. Compared with most existing neural algorithms, the proposed approach effectively makes use of the online estimation of eigenvalue to update the principal eigenvector, which makes the method works...
Next generation of Geometrical Product Specifications (GPS) is the foundation of the technology standards and metrology specifications. Estimation of uncertainty in measurement according to next generation of GPS may improve the reliability of the measurement. A method to estimate the uncertainty in spatial straightness measurement is proposed according to the requirements of next generation of GPS...
In this paper, BP neural network algorithm is applied to camera calibration for the linear structured light 3D digital measurement system and BP network model of camera calibration with double-input double-output is established based on the Levenberg-Marquardt algorithm (LM algorithm). The simulation tests which verify the data of characteristic points obtaining from 3D motion platform show that BP...
As new technologies or products emerge, customer may migrate from a legacy product to a new product. One way to find out who migrate, how migrations look like, and the relationship between the legacy product and the new product is through mining the customer transaction history over time. For these purposes, we propose two customer segmentation procedures to quantify business impact of technology...
In this paper, we design a novel Online Self-constructing Neuro-Fuzzy System (OSNFS) based on the proposed generalized ellipsoidal basis functions (GEBF). Due to the flexibility and dissymmetry of the GEBF, the partitioning made by GEBFs in the input space is more flexible and more economical, and therefore results in a parsimonious neuro-fuzzy system (NFS) with high performance under the online learning...
In this paper, we proposed a functional-link-based neural fuzzy network to improve the traditional TSK-type neural fuzzy network. Besides, an efficient evolutionary learning algorithm, called the Symbiotic Taguchi-based Modified Differential Evolution (STMDE), is proposed for the neural fuzzy networks design. Firstly, in order to avoid trapping in a local optimal solution and to ensure the searching...
Raw material yards at dry bulk terminals act as temporary buffers for inbound and outbound raw materials. Both discharging and charging processes are supported by raw material yards in most cases. Stacker-reclaimers are dedicated equipments in yards for raw material handling. The efficiency of yard operation depends to a great extent on the productivity of stacker-reclaimers. Stacker-reclaimer scheduling...
A stereo pair reconstruction algorithm is proposed which utilizes color mean-shift segmentation on the reference image and local matching based on windows is employed. The scene structure is modeled by a set of planar surface patches, which are needed to be stored for each segment rather than each pixel. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment...
There are many objects and noises in an infrared image with complex sky-sea background, some of these objects and noises exist as points in an image. When a warship appears as some points in an infrared image, it is difficult to identify which point is a target (warship). By analysis these images, this paper presents a method used Fuzzy degree of nearness to identify the target from many objects and...
In this paper, a new neuron model with different output-feedback factor and a neural network model that is composed of output feedback neural model are proposed. And its learning algorithm is derived and proofed in theory. This neural network can learn not only the static knowledge, but can learn dynamic knowledge; not only can remember static information, but can remember dynamic information; so...
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