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Use flue gas wet desulphurization technology to reduce the emissions of sulfur dioxide. The improved BP neural network model based on LM algorithm was established according to the factors that influence sulfur dioxide emissions, and the network weights and threshold value were adjusted repeatedly. The real data obtained from thermal power plants are simulated and verified. The results show that the...
The minimization problem of reconstruction error over large hyperspectral image data is one of the most important problems in unsupervised hyperspectral unmixing. A variety of algorithms based on nonnegative matrix factorization (NMF) have been proposed in the literature to solve this minimization problem. One popular optimization method for NMF is the projected gradient descent (PGD). However, as...
Short-term prediction of water demand provides basic guarantee of water supply system operation and management. In this study, an effective model for daily water demand forecasting is proposed. Firstly, principle component analysis (PCA) is utilized to simplify the complexity and reduce the correlation between influence variables, and the score values of selected principle components (PCs) turn into...
Nowadays, the attacks on the Internet are becoming more complex, advanced and concealed. A large number of security threats arise. The signature-based detection technology is efficient and simple which is widely used for malicious codes detection system. In this paper, we firstly focus on the principle of the method, and summarize the specific steps to implement it, especially feature extraction,...
Frequent pattern mining is playing an increasingly important role in a growing number of real-time data flow scenarios, such as large-scale order stream data, network traffic monitoring, web accessing record stream, and so on. The continuous, unbounded and high speed characteristics of massive data stream are a huge challenge for the current frequent pattern mining approach. The main challenge is...
Offloading the computation-intensive task of mobileinteractive applications into cloudlets has become a popularway to reduce the response time in mobile cloud computingarea. In response to the rapid change of mobile environment, researchers have proposed online offloading decisions for variousapplications. However, the pruning method they used wouldperform poorly for the non-linear topology of applications...
Human detection plays a crucial role in a number of real world applications. Because of the popularity of smart car, Virtual Reality (VR) and other applications, strong demand of real-time detecting rises. The efficiency of a human detection algorithm becomes more crucial than ever before. In this work, a novel human detection framework combining the Histograms of Oriented Gradients (HOG) feature,...
In this paper, a new auxiliary function is proposed for large scale global optimization. For the problems with a lot of local optimal solutions, the proposed auxiliary function can eliminate all local optimal solutions no better than those obtained local optimal solution and find a better local optimal solution. To enhance efficiency and effectiveness of evolutionary algorithms, the proposed auxiliary...
Most nonlinear unmixing algorithms are based on the nonlinear mixing models with different forms. This paper focuses on the well-known generalized bilinear model (GBM). Though the GBM has shown interesting and promising for nonlinear unmixing, currently almost all the GBM-based unmixing algorithms are supervised. That is, the endmembers must be assumed known in advance. This paper develops an unsupervised...
In this paper, we propose a feasible method for solving the NP-hard absolute value equation (AVE) Ax -- |x| = b, which has 2n-solutions. The method mixes differential evolution, K-Means and Simplex Search Method together and achieves an effective balance of exploration and exploitation, denotes SKDE. SKDE execute k-means to gain 2n subgroups from initial individuals. perform DE operation to obtain...
In order to solve the problem about the partition of Petri net model and subnet division, realize the concurrent execution or simulation runs of Petri net system, the partitioning algorithm of parallel subnet of Petri net is proposed. First, as Petri net system has the characteristics of synchronization and concurrence, provide the place-invariant based Petri net model partitioning and subnet division...
ID/IDREF feature makes XML document model become graph structure rather than tree structure, while traditional Twig join algorithms can just process simple queries without ID references. Those queries with ID references often involve attribute node or predicates with expressions which do not exist in traditional Twig pattern, so it is necessary to design the Twig join algorithm for the implement of...
To solve the parallelism algorithm of Petri network system with parallel feature and implementing paralleling control and execution of Petri network, we propose the analysis and algorithm design of Petri network process. Based on employing P-invariants to partition the function of Petri network system, we firstly analyzed the situations of parallelism between processes, checked the effects of the...
Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In this algorithm, the parameter selection is very important on the algorithm performance. Huang proposed a modified...
In this paper, we propose a fast MPI algorithm for Monte Carlo approximation PageRank vector of all the nodes in a graph, named Fast Fibonacci Series-Based Personal PageRank. In the latter paper we will call it FFSB algorithm for short. The basic ideal is very efficiently computing single random walks of a given length starting at each node in a graph. More precisely, we design FFSB, which given a...
Aerial imagery sensors can provide sufficient resolution to sense vehicle locations and movements across broader spatial and temporal scales. In this paper, an approach for collecting and analyzing aerial imagery is given. This paper presents a method to detect vehicle from a moving camera. The detection component involves a cascade of modules. First, road is detected Based on edge detection and blob...
Uncovering the dynamic nature of protein-protein interaction networks is important to understand life at the system-level. However, the large-scale protein interaction data sets are static and unable to capture the changes in the profile of protein. In this paper, we focus on the following questions (1) Can we detangle the dynamic features of PPI networks? (2) Can we effectively detect the overlapping...
Roof segmentation, i.e. separating building roofs, is a key step in deriving building models as it directly influences the precision and accuracy of the final building models. Even though various segmentation methods have been proposed, convincing and completing evaluations of the segmentation results are rarely discussed. This paper proposes several approaches to provide quantitative evaluation of...
Data analyzing and processing are important tasks in cloud computing. The MapReduce framework has been increasingly used to analyze large-scale data over large clusters. Compared with parallel relational database, it has the advantages of excellent scalability and good fault tolerance. However, its performance is not as good as that of parallel relational database. How to efficiently implement join...
Femtocells will be widely employed in the next generation wireless networks since they improve indoor capacity and coverage with low cost and low power characteristics. However since macro cells may have to share the same spectrum with femtocells, resource allocation schemes have been a key challenge to manage interference. In this paper, we propose a novel resource allocation scheme based on cognitive...
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