One of the most critical issues in using service-oriented technologies is the combination of services, which has become an important challenge in the present. There are some significant challenges in the service compo...
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One of the most critical issues in using service-oriented technologies is the combination of services, which has become an important challenge in the present. There are some significant challenges in the service composition, most notable is the quality of service (QoS), which is more challenging due to changing circumstances in dynamic service environments. Also, trust value in the case of selection of more reliable services is another challenge in the service composition. Due to NP-hard complexity of service composition, many metaheuristic algorithms have been used so far. Therefore, in this paper, the honeybee mating optimization algorithm as one of the powerful metaheuristic algorithms is used for achieving the desired goals. To improve the QoS, inspirations from the mating stages of the honeybee, the interactions between honeybees and queen bee mating and the selection of the new queen from the relevant optimization algorithm have been used. To address the trust challenge, a trust-based clustering algorithm has also been used. The simulation results using C# language have shown that the proposed method in small scale problem acts better than particle swarm optimization algorithm, genetic algorithm, and discrete gbest-guided artificial bee colony algorithm. With the clustering and reduction of the search space, the response time is improved;also, more trusted services are selected. The results of the simulation on a large-scale problem have indicated that the proposed method is exhibited worse performance than the average results of previous works in computation time.
SAG machine is an important part of the SABC *** view of the characteristics of many variables,nonlinearity,strong coupling,large hysteresis,time-varying,the traditional control methods are difficult to achieve better...
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ISBN:
(纸本)9781665431293
SAG machine is an important part of the SABC *** view of the characteristics of many variables,nonlinearity,strong coupling,large hysteresis,time-varying,the traditional control methods are difficult to achieve better results,and the introduction of clustering learning algorithm is *** normal operation data of SAG machine is subjected to cluster learning analysis,and compared with the existing operating experience,and self-learning affects the control relationship between the process parameters of its operating conditions,and forming the optimized control rule set,which can be used as the rule base of expert system,instead of the original control method,its operation state is improved,that the cost is reduced,and the energy consumption is saved,and the economic benefit of concentrator is improved.
In vehicular ad hoc networks (VANETs), due to the high dynamics of the vehicles, clustering is an effective way to alleviate the problem of frequent communication interruption. In recent years, many pieces of research...
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ISBN:
(纸本)9781728112206
In vehicular ad hoc networks (VANETs), due to the high dynamics of the vehicles, clustering is an effective way to alleviate the problem of frequent communication interruption. In recent years, many pieces of research have pointed out that clustering can improve the stability of the cluster by using similar mobility patterns of the vehicles. In this paper, we propose a new distributed mobility-based multi-hop clustering algorithm (DMMCA) in highway scenarios. DMMCA uses the vehicle's moving direction, relative speed and relative position to construct the multi-hop cluster. In addition, in order to reduce the overhead of the clustering algorithm, we design a new hello packet rebroadcast mode. Extensive simulation experiments are performed using ns-3 to demonstrate our proposed algorithm. The results show that our proposed algorithm can improve the performance of the cluster in terms of average cluster head duration, average cluster member duration, average state changes. Moreover, the number of rebroadcast hello packets is also reduced.
Massive MIMO system with FDD mode can support very high spatial reuse, however, the improvement of system performance is greatly limited due to the similarity between users and the overhead of uplink CSI feedback. In ...
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ISBN:
(纸本)9781728118468
Massive MIMO system with FDD mode can support very high spatial reuse, however, the improvement of system performance is greatly limited due to the similarity between users and the overhead of uplink CSI feedback. In this paper, a clustering algorithm based on users multi-dimensional features for Massive MIMO System is proposed to mitigate inter-user interference. Specifically, it includes searching and eliminating users with noise spots, analyzing and defining user space-related and non-space-related features, and reducing the dimension of three-dimensional features. Then, inspired by the Affinity propagation (AP) clustering algorithm, we propose the scheme considering the similarity between users for clustering. The simulation results show that the proposed scheme can significantly reduce the inter-user interference while improving the average SINR of users.
In order to accurately extract landslide disaster information from SAR images, we propose a clustering algorithm for landslide detection using multi-temporal fully polarimetric SAR image. By combining Freeman-Durden d...
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ISBN:
(纸本)9781538691540
In order to accurately extract landslide disaster information from SAR images, we propose a clustering algorithm for landslide detection using multi-temporal fully polarimetric SAR image. By combining Freeman-Durden decomposition with H /alpha /A decomposition method, this algorithm makes full use of scattering power and scattering entropy information. Furthermore, a hierarchical method is proposed to overcome the drawback that fuzzy membership function family of multi-region classification cannot always satisfy the constraint conditions to guarantee functional convexity. Such method ensures that the constraint conditions can always be satisfied and improves the accuracy of classification. Finally, the landslide disaster area is accurately extracted from the two classification maps by change detection. The results of the C-band RadarSat-2 data are provided to demonstrate its competitive general performance of image classification.
Big data analysis has penetrated into all fields of society and has brought about profound ***,there is relatively little research on big data supporting student management regarding college and university’s big *** ...
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Big data analysis has penetrated into all fields of society and has brought about profound ***,there is relatively little research on big data supporting student management regarding college and university’s big *** the student card information as the research sample,using spark big data mining technology and K-Means clustering algorithm,taking scholarship evaluation as an example,the big data is *** includes analysis of students’daily behavior from multiple dimensions,and it can prevent the unreasonable scholarship evaluation caused by unfair factors such as plagiarism,votes of teachers and students,*** the same time,students’absenteeism,physical health and psychological status in advance can be predicted,which makes student management work more active,accurate and effective.
This paper proposed a novel flower pollination clustering algorithm, which called NIPC algorithm for arranging data sets into clusters. It starts from the phenomenon of plant aggregation and growth with similar charac...
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ISBN:
(纸本)9781728140940
This paper proposed a novel flower pollination clustering algorithm, which called NIPC algorithm for arranging data sets into clusters. It starts from the phenomenon of plant aggregation and growth with similar characteristics inspired from insect pollination. In this context, the two position updating strategies allows plants to get the most comfortable position. The experiments show that it has a good effect on processing data sets with different sizes, shapes and density compared with other swarm intelligence algorithms.
In this paper, to mitigate frequency selective power fading induced by multipath effect, a clustering algorithm based on k-means is proposed for OFDM-VLC system. The simulation results show that, aided by the k-means ...
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ISBN:
(数字)9781510627710
ISBN:
(纸本)9781510627710
In this paper, to mitigate frequency selective power fading induced by multipath effect, a clustering algorithm based on k-means is proposed for OFDM-VLC system. The simulation results show that, aided by the k-means clustering algorithm, the signal-to-noise ratio (SNR) is improved by more than 7 dB compared to the scheme without k-means clustering algorithm at BER of 3.8x10(-3), the hard decision forward error correction (HD-FEC) limit.
This paper takes the logistics distribution record of Yifeng Weiye Group for the past two years as the basic research unit. By exploring the relationship between data fields, we use the idea of adaptive clustering alg...
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ISBN:
(纸本)9781450360920
This paper takes the logistics distribution record of Yifeng Weiye Group for the past two years as the basic research unit. By exploring the relationship between data fields, we use the idea of adaptive clustering algorithm and spatial clustering analysis to process the attribute data of transportation capacity[8]. Basing on the obtained clustering results, we use Python and PHP technology to optimize the distribution area, and finally design an effective visual expression method to obtain the traffic situation knowledge. We can provide relevant analysis and technical support for enterprises to improve the efficiency of distribution logistics and optimize the structure of the industrial chain.
Next generation cellular systems need efficient content-distribution schemes. Content-sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach for alleviating the burden on the cellular ...
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Next generation cellular systems need efficient content-distribution schemes. Content-sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. In this article, we utilize Content-Centric Networking and Network Virtualization to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multifactor clustering algorithm is proposed for grouping the D2D User Equipment (DUEs) sharing a common interest. The proposed algorithm is evaluated in terms of energy efficiency, area spectral efficiency, and throughput. The effect of the number of clusters on these performance parameters is also discussed. The proposed algorithm has been further modified to allow for a tradeoff between fairness and other performance parameters. A comprehensive simulation study demonstrates that the proposed clustering algorithm is more flexible and outperforms several classical and state-of-the-art algorithms.
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