Parallelizing Backpropagation Neural Network Using MapReduce and Cascading Model

Liu, Yang; Jing, Weizhe; Xu, Lixiong

doi:10.1155/2016/2842780

Cited by 24 publications

(15 citation statements)

References 22 publications

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“…Nguyen and Giordano [16] recommended a socially-based routing algorithm using the location prediction of users, where the data transmission in this strategy is divided into two situations-i.e., the destination is an occasional contact node or a frequent contact node. This algorithm adopts a backpropagation neural network (BNN) model [24] to predict the future meeting probability of nodes, and the message carrier makes a suitable decision on when and where to transmit messages to the relay node. In this algorithm, the mobile periodicity of nodes is creatively adopted to predict the location and time of node encounters.…”

Section: The Proposed Context-ignorant Routing Algorithmsmentioning

confidence: 99%

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

Liu

Chen

et al. 2018

Symmetry

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At the dawn of big data and 5G networks, end-to-end communication with large amounts of data between mobile devices is difficult to be implemented through the traditional face-to-face transmission mechanism in social networks. Consequently, opportunistic social networks proposed that message applications should choose proper relay nodes to perform effective data transmission processes. At present, several routing algorithms, based on node similarity, attempt to use the contextual information related to nodes and the special relationships between them to select a suitable relay node among neighbors. However, when evaluating the similarity degree between a pair of nodes, most existing algorithms in opportunistic social networks pay attention to only a few similar factors, and even ignore the importance of mobile similarity in the data transmission process. To improve the transmission environment, this study establishes a fuzzy routing-forwarding algorithm (FCNS) exploiting comprehensive node similarity (the mobile and social similarities) in opportunistic social networks. In our proposed scheme, the transmission preference of the node is determined through the fuzzy evaluation of mobile and social similarities. The suitable message delivery decision is made by collecting and comparing the transmission preference of nodes, and the sustainable and stable data transmission process is performed through the feedback mechanism. Through simulations and the comparison of social network algorithms, the delivery ratio in the proposed algorithm is 0.85 on average, and the routing delay and network overhead of this algorithm are always the lowest.

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Section: The Proposed Context-ignorant Routing Algorithmsmentioning

confidence: 99%

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

Liu

Chen

et al. 2018

Symmetry

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“…The neural networks are broadly classified as feed-forward network and recurrent network (Yu et al, 2002;Liu et al, 2016). The neurons with unidirectional connections are ordered into layers for designing feed-forward networks whereas recurrent networks have loops with feedback connections.…”

Section: Outline Of Neural Networkmentioning

confidence: 99%

A Novel Channel State Prediction Technique for Overlay Cognitive Radio-based Emergency Sensor Networks

Chatterjee¹,

Chakraborty²,

Saha

2018

IJKEDM

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For overlay cognitive radio (CR), this paper proposes a knowledge-based spectrum prediction technique using artificial neural network. This is targeted for CR-based emergency sensor networks in real life applications, where extremely reliable data transmission is mandatory. The technique operates in two steps: 1) identification of idle states in primary user bands; 2) prediction of noise level of the idle bands. The goal is to select a less noisy vacant band among the detected idle bands. The system is analysed under both Gaussian mixer noise (GMN) distribution and additive white Gaussian noise (AWGN) by predicting the current state of the channel in low SNR environment. Simulation results using MATLAB R2015b show satisfactory values for probability of false alarm (0.17 and 0.3), and probability of misdetection (0.12 and 0.25) for AWGN and GMN, respectively.

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“…In terms of comparing the classification accuracy, back propagation neural network (BPNN) is also implemented. The parameters of the neural network is configured according to the research . Figures and show the results.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…The parameters of the neural network is configured according to the research. 26 Figures 7 and 8 show the results. half of which is training data and the rest is testing data.…”

Section: Algorithm Precisionmentioning

confidence: 99%

MapReduce‐based parallel GEP algorithm for efficient function mining in big data applications

Liu

et al. 2017

Concurrency and Computation

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Summary Gene expression programming (GEP) algorithm is one of the most effective function mining algorithms in enabling the mathematical equation fitting for the input dataset. However, GEP algorithm encounters low efficiency issue in big data processing due to large overhead in its evolution when it handles the large‐scale data. In order to solve the issue, this paper presents two parallelized GEP algorithms using MapReduce. Based on data separation, the first algorithm aims at speeding up the large‐scale classification. However, it is lack of ability to output the mined equation explicitly. Therefore, based on the further improvements of the first algorithm, the second parallelized GEP algorithm aims at mining the equation efficiently and also outputs the equation explicitly and directly. The experimental results show that both algorithms are effective for processing large volume of data.

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Parallelizing Backpropagation Neural Network Using MapReduce and Cascading Model

Cited by 24 publications

References 22 publications

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

FCNS: A Fuzzy Routing-Forwarding Algorithm Exploiting Comprehensive Node Similarity in Opportunistic Social Networks

A Novel Channel State Prediction Technique for Overlay Cognitive Radio-based Emergency Sensor Networks

MapReduce‐based parallel GEP algorithm for efficient function mining in big data applications

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