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The algorithms on learning to rank can traditionally be categorized as three classes including point-wise, pair-wise and list-wise. In our work, we focus on the regression-based method for the multi-partite ranking problems due to the efficiency of the point-wise methods. We proposed two ranking algorithms with the real AdaBoost and the discrete AdaBoost, which compute the expectation of the ratings...
This paper analyses the defections of traditional support vector machine (for short SVM). According to the characteristics of grain information on the web, a multi-class classification method based on Huffman binary tree SVM (for short HBT-SVM) is presented for grain information classification. Compared with existing SVM methods, this method has higher computation efficiency. The experimental results...
In this paper we report on flexible a-Si:H solar cells prepared on polyethylene naphthalate (PEN) substrates using p-type hydrogenated nanocrystalline silicon thin films (p-nc-Si:H) as the window layer. The p-nc-Si:H films were prepared at low temperature (150 °C) using trimethylboron (TMB) as a dopant gas. The influence of the silane concentration (SC) on the electrical and structural properties...
Multi-label learning is increasingly required by many domains such as text categorization and scene classification. Learning vector quantization (LVQ) offers a simple, power and scalable algorithm for the single-label learning. In this work, we adapt LVQ to solve the multi-label problems called ML-LVQ. It once adjusts two prototypes for each label of the example to minimize the ranking loss approximately...
The CICC (cable-in-conduit conductor) in ITER (International Thermal-nuclear Experimental Reactor) will run in high-current, fast transient magnet field and complex environment. In response to the impact of magnet fields above 10 T, the Nb3Sn conductor has been introduced. However, the AC (alternating current) loss mechanism of Nb3Sn conductor on strain has not been explored. So, it is necessary to...
Five different methods were tested and compared to prepare danofloxacin mesylate liposomes, the ammonium sulfate gradient method with freeze-thawing steps was validated as the best one; the optimal preparation condition confirmed by orthogonal experiment was as follows: EPC-CH ratio was 3 : 2 and 2.6% SA was added to gain the positive electricity; drug-lipoid was 2 : 5, the concentration of ammonium...
C4.5 is a popular classification method which can give the explainable and intuitional classification rules. But it is prone to overfitting due to the data noise or the distribution of the instances. In this paper, we proposed a new decision tree method with the support vector machine (SVM-DTR), which make the surface of the decision tree to discriminate the instances from the different categories...
To address the parameter optimization problem of plate color recognition, two approaches based on IA (immune algorithm) and GA (genetic algorithm) are proposed respectively. Theoretical comparison of IA and GA is first made. Then experimental comparison of the two algorithms is given by using them to perform the parameter optimization task for color recognition of license plates. For plate color recognition...
To improve accuracy and adaptability, this paper presents a learning algorithm for color recognition of license plates. For three components of the hue-saturation-value (HSV) color space, different membership functions were defined to calculate their fuzzy degrees. Through the weighted fusion of the three membership degrees, a single map was produced to be the classification function for color recognition,...
Kernel principal component analysis (KPCA) is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components in feature space. But the method is infeasible for large-scale data set because of the storage and computational problem. To overcome these disadvantages, an efficient iterative method of computing kernel principal components...
A novel vision method is proposed to correct the robot heading angles in this paper. The salient feature point with known relative position to the target was chosen as the reference point. And the pose adjustment quantities of the robot were determined according to the navigation curve which is composed of the images of the reference point. This algorithm uses only one reference point and has the...
In this paper, to solve the problem of feedback cost and performance loss for precoded spatial multiplexing with limited feedback, an novel nonlinear detection method based on limited feedback for precoded vblast is proposed, the corresponding criteria is used for select optimal codeword from the Grassmannian codebook at the receiving according to the channel state information, and feedback the precoding...
During the storage of grain, its quality can be influenced by temperature, humidity, oxygen, microorganisms, insects and other factors. It is necessary to protect the storage quality of grain through real-time monitoring these parameters and analyzing their influences. An algorithm is proposed based on flexible logic centralized fusion to study the evaluation method of overall temperature in grain...
Attribute importance ranking still is a key problem required to be solved for the classification problem. The lack of efficient heuristic information is the fundamental reason that affects the attribute selection in data mining. In this paper, to determining the importance level of the attributes, a new measure based on partial derivative distribution of the classification hypersurface output corresponding...
Building heterogeneous multi-core processor is desirable because it may provide high parallel performance such as instruction level parallelism (ILP) and thread-level parallelism (TLP). However, most existing operating system and parallel applications can't make good use of this heterogeneity because it arises dramatic instability sometimes, especially when the work of different core is unbalanced...
Considering the problem of feedback cost and performance loss for precoded spatial multiplexing MIMO OFDM with limited feedback, an improved nonlinear detection method based on perturbation codebook with limited feedback for precoded vblast is proposed, the corresponding criteria is used for select optimal codeword from the Grassmannian codebook at the receiving according to the channel state information,...
Considering the problem of feedback cost and performance loss for precoded spatial multiplexing with limited feedback, an novel nonlinear detection method based on perturbation codebook with limited feedback for precoded vblast is proposed, the corresponding criteria is used for select optimal codeword from the Grassmannian codebook at the receiving according to the channel state information, selecting...
The reasonable division of attribute spaces is a core problem in the decision tree construction and the rule extraction, which directly influences the effectiveness of the construction of decision trees. In this paper, a new two-dimension analysis method for the attribute space division is proposed, which not only reduces the analysis complexity, but also improves the efficiency of attribute division...
Color recognition of license plates is an important step to License Plate Recognition (LPR) system. In order to perform color recognition more effectively, an algorithm based on Naive Bayesian approach is proposed in this paper. To improve the efficiency of color recognition, the multiclass problem is converted into two binary problems based on the reverse color information of plate images. Color...
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