Hyperspectral image classification is an important part of the hyperspectral remote sensing information processing. The Iterative Selforganizing Data Analysis Techniques algorithm (ISODATA) clustering algorithm which ...
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ISBN:
(纸本)9781479958368
Hyperspectral image classification is an important part of the hyperspectral remote sensing information processing. The Iterative Selforganizing Data Analysis Techniques algorithm (ISODATA) clustering algorithm which is an unsupervised classification algorithm is considered as an effective measure in the area of processing hyperspectral images. In this paper, an improved ISODATA algorithm is proposed for hyperspectral images classification. The algorithm takes the maximum and minimum spectrum of the image into consideration and determines the initial cluster center by the stepped construction of spectrum accurately. The classification experiment results show that using the improved ISODATA algorithm can determine the initial cluster number adaptively. In comparison with the SAM (Spectral Angle Mapper) algorithm and the original ISODATA algorithm, a better performance of the proposed ISODATA method is shown in the part of results.
In this paper, a method is proposed to solve the displacements and distortions, which are caused by inaccurate calibration in the low-level fusion. Compared with existing methods, the proposed method does not rely on ...
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ISBN:
(纸本)9781509023974
In this paper, a method is proposed to solve the displacements and distortions, which are caused by inaccurate calibration in the low-level fusion. Compared with existing methods, the proposed method does not rely on any specified environmental feature and can be applied to a variety of scenarios. To implement it, twice clustering processes are applied to segment the input point cloud, and an iterative closest point (ICP) algorithm is used to iterate and correct the corresponding partitions. Furthermore, we also quantify an index to evaluate the result of correction and provide some simplified constraints to improve the measurement accuracy. Finally, the effectiveness of the proposed methods is verified by the result of 3D reconstruction.
With the emergence of the big data age, how to get valuable hot topic from the vast amount of digitized textual materials quickly and accurately has attracted more and more attention. This paper proposes a parallel Tw...
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ISBN:
(纸本)9781509040940
With the emergence of the big data age, how to get valuable hot topic from the vast amount of digitized textual materials quickly and accurately has attracted more and more attention. This paper proposes a parallel Two-phase Micmac Hot Topic Detection (TMHTD) method specially design for microblogging in "Big Data" environment, which is implemented based on Apache Spark cloud computing environment. TMHTD is a distributed clustering framework for documents sets with two phases, including micro-clustering and macro-clustering. In the first phase, TMHTD partitions original data sets into a group of smaller data sets, and these data subsets are clustered into many small topics, producing intermediate results. In the second phase, the intermediate results are integrated into one, further clustered, and achieve the final hot topic sets. To improve the accuracy of the hot topic detection, an optimization of TMHTD is proposed. To handle large databases, we deliberately design a group of MapReduce jobs to concretely accomplish the hot topic detection in a highly scalable way. Extensive experimental results indicate that the accuracy and performance of TMHTD algorithm can be improved significantly over existing approaches.
In this paper,a new attempt has been made using fuzzy set to construct intuitionistic fuzzy set basing on fuzzy entropy.A new intuitionistic fuzzy set generator is defined,which obtained hesitation degree by applying ...
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In this paper,a new attempt has been made using fuzzy set to construct intuitionistic fuzzy set basing on fuzzy entropy.A new intuitionistic fuzzy set generator is defined,which obtained hesitation degree by applying so-called 'complement' to *** relationship between fuzzy entropy and hesitation degree of intuitionistic fuzzy set is *** method to calculate hesitation degree of intuitionistic fuzzy set basing on fuzzy entropy is *** this proposed constructing method,edge detection has been carried out,and the results have been found better with respect to previous methods.
In order to conserve energy in wireless sensor networks (WSNs), sensor nodes are partitioned into clusters. clustering algorithm provides an effective way to extend the network lifetime of WSNs. The operation of clust...
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ISBN:
(纸本)9781509004799
In order to conserve energy in wireless sensor networks (WSNs), sensor nodes are partitioned into clusters. clustering algorithm provides an effective way to extend the network lifetime of WSNs. The operation of clustering algorithm is divided into cluster heads (CHs) selection phase and cluster formation phase. However, most of the previous researches have focused on CHs selection, and have not considered the cluster formation phase, which is important problem in WSNs and can drastically affect the network lifetime in WSNs. In this paper, cluster formation using fuzzy logic (CFFL) approach has been proposed to prolong network lifetime and reduce energy consumption in WSNs. this approach uses fuzzy logic in the formation cluster phase, two fuzzy parameters are used. These parameters are residual energy which is energy level of each CH and closeness to base station (BS) which is the distance between the CH and the BS. Simulation results show that the proposed approach consumes less energy and prolongs the network lifetime compared with Low Energy Adaptive clustering Hierarchy (LEACH) protocol.
Owing to the limited resources of the sensor nodes, designing energy-efficient routing mechanism to prolong the overall network lifetime becomes one of the most important technologies in wireless sensor networks (...
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ISBN:
(纸本)9781457715860
Owing to the limited resources of the sensor nodes, designing energy-efficient routing mechanism to prolong the overall network lifetime becomes one of the most important technologies in wireless sensor networks (WSNs). As an active branch of routing technology, cluster-based routing protocols have proven to be effective in network topology management, energy minimization, data aggregation and so on. In this paper, we present a survey of stateof-the-art routing techniques in WSNs. We first outline the clustering architecture in WSNs, and classify the proposed approaches based on their objectives and design principles. Furthermore, we highlight the challenges in clustering WSNs, including rotating the role of cluster heads, optimization of cluster size and communication mode, followed by a comprehensive survey of routing techniques. Finally, the paper concludes with possible future research areas.
In order to prolong the network lifetime, energyaware protocols should be designed to adapt the characteristic of wireless sensor networks. clustering is a kind of key routing technique used to reduce energy consumpti...
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In order to prolong the network lifetime, energyaware protocols should be designed to adapt the characteristic of wireless sensor networks. clustering is a kind of key routing technique used to reduce energy consumption. In this paper, a new clustering algorithm MNLC (Maximum Network Lifetime clustering algorithm) for energy heterogeneous sensor networks is proposed. The algorithm uses distributed, dynamic clustering process. On the one hand, cluster-head selection is primarily determined by the residual energy level of each node, on the other hand, the ordinary nodes select which cluster to join according to the remaining energy level of the candidate cluster-heads and the parameter of communication cost in a cluster, so as to effectively achieve the balanced distribution of energy loss in the network. Simulation results show that MNLC could better implement load balance and prolong the network lifetime in heterogeneous environments.
The main constraints of a wireless sensor network are limited battery power and short lifetime. One of the main reasons of energy consumption is the data transmission. Each node senses the data and sends them over to ...
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ISBN:
(纸本)9781479987931
The main constraints of a wireless sensor network are limited battery power and short lifetime. One of the main reasons of energy consumption is the data transmission. Each node senses the data and sends them over to the base station. The sensor data fusion reduces the volume of message transmission and makes the network energy efficient. In this paper, we have presented a data fusion algorithm which minimizes the computation cost, communication cost and in the same way it reduces the consumption of energy. The algorithm derives the state of the network using the concept of priority of the sensors. The proposed algorithm gives a better false alarm rate than the existing data fusion algorithm used in the coal mine.
With the increase of the number of railway container manufacturers, the average maintenance cost of each factory's container is uneven. In order to evaluate the quality of the container, it is necessary to do clus...
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With the increase of the number of railway container manufacturers, the average maintenance cost of each factory's container is uneven. In order to evaluate the quality of the container, it is necessary to do cluster analysis of railway container stations, thus classify the container by the different stations the containers go through. This paper is based on the data of container application for nearly 10 years and constructs the index system of station cluster analysis. Through the cargo ticket and maintenance information of the container, the index data of the station is obtained. Then compares the different results of each clustering algorithm and selects the best clustering algorithm. Finally analyze the data characteristics and the reason of grouping results.
With the rapid development of computer vision technology and image processing technology,image retrieval has also developed from simple text information query to complex content-based image retrieval,which is a proces...
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With the rapid development of computer vision technology and image processing technology,image retrieval has also developed from simple text information query to complex content-based image retrieval,which is a process from low-level to high-level *** paper mainly focuses on the content-based image retrieval method,to analyze the application of an optimized PAM algorithm based on fireworks particle swarm optimization in image retrieval.
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