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Endmember extraction is a critical step of spectral unmixing. In this paper, a novel endmember extraction algorithm based on evolutionary multi-objective optimization is proposed for hyperspectral remote sensing images. In the proposed method, endmember extraction is modeled as a multi-objective optimization problem. Then the root mean square error between the original image and its remixed image...
The detection of shared community structure in multilayer network is an interesting and important issue that has attracted many researches. Traditional methods for community detection of single layer networks are not suitable for that of multilayer networks. In a previous work, the authors modeled the community discovery problem in multilayer network as a multiobjective one and devised a genetic algorithm...
Evolutionary multi-tasking is a novel concept where algorithms utilize the implicit parallelism of population-based search to solve several tasks efficiently. In last decades, multi-task learning, which harnesses the underlying similarity of the learning tasks, has proved efficient in many applications. Extreme learning machine is a distinctive learning algorithm for feed-forward neural networks....
In this paper, two multi-objective clustering ensemble algorithms are proposed named MOCLED and MOCNCD. MOCLED is different from MOCLE on three points. First, different clustering algorithms are used to produce some new individuals in evolutionary process. Second, a new screening mechanism is added. In each generation, the worst individual is replaced by the best individual. Third, a new objective...
Band selection is a crucial preprocessing step for hyperspectral image classification, which is a classic feature selection method. Feature selection is designed to select feature subsets to represent the whole feature space. For feature selection, two crucial issues need to be handled: preserving information and redundancy reducing. In this paper, a novel feature selection method for hyperspectral...
According to the medium and long term development planning of railway networks, China will built “eight vertical and horizontal” high speed railway network during 13th five-year. With the rapid development of mobile smart terminals, the rail dedicated communication system using GSM-R system cannot satisfy the passengers' communication requirement. As high frequency communication has been considered...
Wireless visual sensor networks comprise a large number of camera-equipped sensor devices and obtain visual information from field of interest. In a Wireless visual sensor network, there exist visual correlation characteristics among images observed by cameras with overlapped field of views. To describe those characteristics, the conventional method is based on image processing. However, it is too...
The goal of this paper is to understand the patterns of mobile traffic consumption and reveal the correlations between human activities and mobile traffic patterns in the urban environment. This task is nontrivial in terms of three challenges: the complexity of mobile traffic consumption in large urban scale, the disturbance of abnormal events, and lack of prior knowledge about urban traffic patterns...
Due to the strong randomness and intermittency of photovoltaic (PV) power output, accurate PV power output forecast becomes more and more important for system reliability, meanwhile it can promote large-scale PV deployment. In this paper, a novel PV power output forecast model based upon weather type clustering and support vector machines (SVM) regression is proposed. Firstly, on the basis of calculated...
Advance selling is a new business model, we study optimal advance selling inventory decision of two competing firms offering homogeneous new products on the advance selling platform considering strategic customers, we use Stackelberg and Cournot game model. This paper considers a two-period model, the first period is advance selling which is possible at a discount price, regular price or premium price,...
In this paper, we consider to apply a joint defrag-mentation (DF) of spectrum and computing resources in the inter-datacenter (inter-DC) networks built over elastic optical infrastructure based on the optical orthogonal frequency-division multiplexing (O-OFDM) technology. We propose joint DF algorithms that consist of a request selection strategy to select active requests for reconfiguring and an...
We propose and experimentally demonstrate a control-plane framework to realize online spectrum defragmentation (DF) in software-defined elastic optical networks. Experimental results show that the spectrum DF enabled by OpenFlow reduces the blocking probability effectively.
We investigate parallel defragmentation and propose a novel algorithm to achieve effective parallelization of the connection reconfigurations with a conflict graph. Simulation results show that the algorithm can effectively reduce the latency of traffic migrations.
Bandwidth defragmentation, i.e., the operation to reconfigure existing connections for making the spectrum usage less fragmented and less misaligned, has recently been recognized as one of the most important features for elastic optical networks (EONs). In this paper, we propose a novel comprehensive bandwidth defragmentation algorithm that considers the problems of 1) When to defragment? 2) What...
We investigate the principle of how dynamic service provisioning fragments the spectral resources on links along a path, and propose corresponding RMSA algorithms to alleviate spectrum fragmentation in dynamic network environments.
We propose several algorithms to achieve hitless bandwidth defragmentation using spectrum retuning in elastic optical networks. Two retuning techniques, spectrum sweeping and hop tuning, are studied. Simulation results show that the hop tuning technique achieves better defragmentation performance.
We propose intelligent timing and object selection algorithms for adaptive spectrum defragmentation in EONs with time-varying traffic. The simulation results show that the algorithms can stabilize and reduce bandwidth blocking probability (BBP) effectively with the minimum number of connection reconfigurations.
We formulate fragmentation ratio to quantify bandwidth fragmentation, and propose two fragmentation-aware RSA algorithms to alleviating it in both static planning and dynamic provisioning of O-OFDM networks. Simulation results indicate that the proposed RSA algorithms outperform two existing ones.
Ad hoc routing protocols can be divided into flat and hierarchical routing. One typical way to build hierarchy is to group mobile nodes into clusters, thus decrease routing space and improve network performance. Mobility models also affect the performance of ad hoc routing protocols and can be divided into entity mobility and group mobility models. This paper first studies the performance of flat...
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