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According to the noise and overlapping characteristics of agricultural irrigation water quality monitoring data for the comprehensive evaluation may bring about the boundary fuzzy problem. This paper proposes an improved Genetic Algorithm (GA) to avoid premature convergence, the global optimal solution of the function of the Projection Pursuit (PP) function is used as the comprehensive evaluation...
AdaBoost is one of the most popular algorithm for classification and has been successfully used for text classification, face detection and tracking. However noise sensitivity is regarded as a major disadvantage and previous works show that AdaBoost will be overfitting when dealing with the data sets with noisy data. To improve the noise tolerance of conventional AdaBoost, this paper proposed a preprocessing...
The Ray-Casting algorithm is an important method for fast real-time surface display from 3D medical images. Based on Ray-Casting algorithm, a novel parallel Ray-Casting algorithm is proposed in this paper. A novel operation is introduced and defined as a star operation, and star operations can be computed in parallel in the proposed algorithm compared with the serial chain of star operations in the...
In classification, a large number of features often make it difficult to select appropriate classification features. In such situations, feature selection or dimensionality reduction methods play an important role in classification. ReliefF algorithm is one of the most successful filtering feature selection methods. In this paper, some shortcomings of the ReliefF algorithm are improved, on the problem...
Kernel learning is an important learning framework in machine learning, whose main idea is a mapping from input space to feature space induced by kernel function which yields a linear separation problem in the feature space. However, the generalization ability of kernel learning, which may lead to over-fitting of training data, has not been formally taken into consideration in previous literatures...
The Discrete Particle Swarm Optimization (DPSO) has little parameters and high convergent capability of the global optimizing. Based on the existing PSO-based classification system we constructed a new classification system based on Discrete PSO. We used the variable-length method to represent particle in the process of operation, represent rule set in a reasonable way and do some appropriate cut,...
To overcome the defect of slow convergence speed, precocity and stagnation in the classical ACO algorithm,the authors propose an Improved Ant System Algorithm Based on PPL to solve TSP according to pheromone updating features of Ant System algorithm, combined with PPL (Parallel Pattern Library) parallel programming idea. The new algorithm combines three different pheromone update methods to make a...
This paper puts forward a least significant bit (LSB) matching steganography detection method based on statistical modeling of pixel difference distributions. Based on the Laplacian model of pixel difference distributions, this paper proposes a method to estimate the number of the zero difference value using the number of non-zero difference values from stego-images, and uses the relative estimation...
Intrusion of network which couldn't be analyzed, detected and prevented may make whole network system paralyze while the abnormally detection can prevent it by detecting the known and unknown character of data. A mixed fuzzy clustering algorithm that uses Quantum-behaved Particle Swarm Optimization (QPSO) algorithm and combines with Fuzzy C-means (FCM) is adopted in this paper and used in abnormally...
In this paper, a new steganalytic method based on statistical distribution of pixel differences is proposed, which is designed to detect the presence of spatial LSB matching steganography in high-resolution natural images. This paper establishes a statistical model for the distribution of pixel differences in natural images based on the Laplacian distribution and estimates the number of zero pixel...
Clustering support vector machines (CSVM) is proposed in this paper for unlabeled data classification. It is often for us to deal with a large number of data which are wholly unlabeled, e.g., classifying them, and it is impractical for us to label these data manually. Clustering algorithms can be used to generate labels for this kind of data. The global k-means clustering algorithm, the fast global...
SMS has become an indispensable tool in people's life. How to help people effectively anti spam SMS and create a healthy, harmonious and ordered environment has become a new research hotspot. On the basis of learning Bayesian learning theory, this thesis mainly researches Bayesian classification model and Bayesian decision based on the minimum risk.
The purpose of this paper is to improve recognition rate of off-line handwritten character recognition system.We apply the statistical characteristics of the percentage of pixels and structural characteristics of boundary chain code of character projection, after train based on HMM to obtain corresponding parameters, then integrate different classifiers through the Bagging algorithm in Voting method...
The human brain is born of memory ??forgotten" mechanism, all information in the way to forget, some precious synchronous degradation memory disappear in history. Constructing a human individual memory database is a good way of being rich for characteristic resource, and could reduce the losses of human forgetting, it would have far-reaching influence about "non-matter cultural heritage...
As Web forum has become an enormous collection of highly valuable opinions and commentaries, more and more researchers express strong interests on it. However, most of them pay attention to the forum reviews rather than the posts themselves. In this paper we focus on recognizing the diversified opinions of different threads on the same topic from Chinese Web forums. First, we congregate the Web forum...
It is necessary to eliminate cluttered information in Web pages, such as navigation bars, related readings, copyright notices, since they can cause additional burden to search engines. In this paper, a Web page is treated as a sequence of content cells, where each cell owns its score according to our Mountain Model. Primary content cells are distinguished from those cluttered content cells by the...
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