Application of DBN deep learning algorithm in anti stealing electricity system by Dandan LI, Bingyu GE, Wenwen HUANG, Lei XIE, Shengqi QIAN

“…With the development of economy,the electric power demand increases gradually,but because of the relative backwardness in the automation of electricity,the phenomenon of electric stealing is common.But the traditional anti electric stealing means generally centered around how to strengthen the technical transformation of the electric energy metering device,and the management efficiency is low.The purpose of deep learning is to use the method of constructing the multi-layer neural network model.To learn the potential features of image,text,voice and other data,it also has good effect on the classification problem.The successful application of the deep learning algorithm in many complex fields provides a new effective way to solve the problem of anti stealing electricity.The structure and learning algorithm of DBN and the anti-stealing model based on DBN algorithm was mainly introduced.Finally,experiments were carried out and the results were analyzed.…”
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Multimedia Vision Improvement and Simulation in Consideration of Virtual Reality Reconstruction Algorithms by Jing He

“…Due to the large noise and many discrete points of the image in the traditional image reconstruction process, the reconstruction quality of the image deviates greatly from the actual target. …”
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Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm by Guimei Gu, Yu Zhao, Xin Zhang

“…This algorithm integrates the advantages of kinetic energy method, effective independence method, modal assurance criterion (MAC), and many other optimal methods. …”
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Improved ant colony optimization algorithm for solving constraint satisfaction problem by HANGYong-gang Z, HANGSi-bo Z, UEQiu-shi X

“…The traditional backtracking algorithm was less efficient on solving large-scale constraint satisfaction problem,and more difficult to be solved within a reasonable time.In order to overcome this problem,many incompleteness algo-rithms based on heuristic search have been proposed.Two improvements based on ant colony optimization meta-heuristic constraint solving algorithm were presented:First,arc consistency checks was done to preprocess before exploring the search space,Second,a new parameter setting scheme was proposed for ant colony optimization to improve the effi-ciency of the search.Finally,the improved algorithm is applied to solve random problems and combinatorial optimization problems.The results of the experiment have showed its superiority.…”
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An Implementable First-Order Primal-Dual Algorithm for Structured Convex Optimization by Feng Ma, Mingfang Ni, Lei Zhu, Zhanke Yu

“…Many application problems of practical interest can be posed as structured convex optimization models. …”
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Heterogeneous Resource Allocation Algorithm for Ad Hoc Networks with Utility Fairness by Bing-Qing Han, Guo-Fu Feng, Yi-Fei Chen

“…In this paper, a novel heterogeneous resource allocation algorithm (HRA) is presented for ad hoc networks, supporting both elastic and inelastic traffic. …”
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A Mahalanobis Hyperellipsoidal Learning Machine Class Incremental Learning Algorithm by Yuping Qin, Hamid Reza Karimi, Dan Li, Shuxian Lun, Aihua Zhang

“…A Mahalanobis hyperellipsoidal learning machine class incremental learning algorithm is proposed. To each class sample, the hyperellipsoidal that encloses as many as possible and pushes the outlier samples away is trained in the feature space. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…Machine learning is gaining importance in many different areas of the economy. One of those areas is the prediction and prevention of consumer churn. …”
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PREDICTION OF TELECOM SERVICES CONSUMERS CHURN BY USING MACHINE LEARNING ALGORITHMS by Edin Osmanbegović, Anel Džinić, Mirza Suljić

“…Machine learning is gaining importance in many different areas of the economy. One of those areas is the prediction and prevention of consumer churn. …”
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Personalization in Mobile Activity Recognition System Using -Medoids Clustering Algorithm by Quang Viet Vo, Minh Thang Hoang, Deokjai Choi

“…Nowadays mobile activity recognition (AR) has been creating great potentials in many applications including mobile healthcare and context-aware systems. …”
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Detecting DDoS attack based on compensation non-parameter CUSUM algorithm by YAN Fen1~3, CHEN Yi-qun3, HUANG Hao1, YIN Xin-chun3

“…t,calculated the ratio of the number of unacknowledged segments and the number of all segments.Then,the statistical sequence based on time came into being.After that,an improved non-parameter recursive CUSUM algorithm was used to detect attack effi-ciently on line.In this procedure,the suspicious packets were also recorded.Experiments prove that this algorithm is fast and efficient.It has low false-positive rate and could adapt to more complex network environments.In addition,it is helpful to attack analysis and tracing.…”
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Newton-Krylov Type Algorithm for Solving Nonlinear Least Squares Problems by Mohammedi R. Abdel-Aziz, Mahmoud M. El-Alem

“…The minimization of a quadratic function within an ellipsoidal trust region is an important subproblem for many nonlinear programming algorithms. When the number of variables is large, one of the most widely used strategies is to project the original problem into a small dimensional subspace. …”
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Application of the Artificial Bee Colony Algorithm for Solving the Set Covering Problem by Broderick Crawford, Ricardo Soto, Rodrigo Cuesta, Fernando Paredes

“…Here, we present a novel application of the artificial bee colony algorithm to solve the non-unicost set covering problem. …”
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Methods and Algorithms for Flexible Job Shop Scheduling − A State of the Art by Guliashki Vassil, Kirilov Leoneed, Marinova Galia

“…The Job Shop Scheduling Problem (JSSP) attracts many researchers due to its combinatorial nature and its discovery in numerous practical applications. …”
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Designing an algorithm to detect depression in users: A quantitative correlational study. by Hodan, T.

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Deduplication algorithm based on condensed nearest neighbor rule for deduplication metadata by Wen-bin YAO, Peng-di YE, Xiao-yong LI, Jing-kun CHANG

“…Building effective deduplication index in the memory could reduce disk access times and enhance chunk fingerprint lookup speed,which was a big challenge for deduplication algorithms in massive data environments.As deduplication data set had many samples with high similarity,a deduplication algorithm based on condensed nearest neighbor rule,which was called Dedup²,was proposed.Dedup²uses clustering algorithm to divide the original deduplication metadata into several categories.According to these categories,it employs condensed nearest neighbor rule to remove the highest similar data in the deduplication metadata.After that it can get the subset of deduplication metadata.Based on this subset,new data objects will be deduplicated based on the principle of data similarity.The results of experiments show that Dedup²can reduce the size of deduplication data set more than 50% effectively while maintain similar deduplication ratio.…”
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A Novel Image Mosaicking Algorithm for Wireless Multimedia Sensor Networks by Zhiyuan Li, Weiting Kong, Yongzhao Zhan, Junlei Bi

“…After the image registration, the adaptive weighted average algorithm is proposed to do the image fusion. The simulation experiments show that compared with homogeneous algorithms, the IMBPW algorithm has higher real-time and fast convergence speed. …”
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CSI feedback algorithm based on deep unfolding for massive MIMO systems by Yong LIAO, Gang CHENG, Yujie LI

“…In order to solve the problem that the channel state information (CSI) feedback algorithm based on deep learning in massive MIMO systems at present had too many parameters to be trained and could not be explained well, two CSI feedback algorithms based on depth expansion were proposed.The first one was approximate message delivery (AMP) algorithm based on learnable parameters.The learnable parameters in deep learning were used to replace the threshold value of the threshold function in the AMP algorithm and the parameters of the Onsage correction term.The nonlinear ability of threshold function in dealing with non-strict sparse data was enhanced.The other was the AMP algorithm based on convolutional network, which replaced the threshold function module with the convolutional residual learning module, and used the module to remove the Gaussian random noise generated by each iteration of the AMP algorithm.Simulation results show that the proposed two algorithms have better CSI feedback performance than AMP algorithm, and the AMP algorithm based on convolutional network has better CSI reconstruction performance than the representative method based on deep learning.…”
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Deduplication algorithm based on condensed nearest neighbor rule for deduplication metadata by Wen-bin YAO, Peng-di YE, Xiao-yong LI, Jing-kun CHANG

“…Building effective deduplication index in the memory could reduce disk access times and enhance chunk fingerprint lookup speed,which was a big challenge for deduplication algorithms in massive data environments.As deduplication data set had many samples with high similarity,a deduplication algorithm based on condensed nearest neighbor rule,which was called Dedup²,was proposed.Dedup²uses clustering algorithm to divide the original deduplication metadata into several categories.According to these categories,it employs condensed nearest neighbor rule to remove the highest similar data in the deduplication metadata.After that it can get the subset of deduplication metadata.Based on this subset,new data objects will be deduplicated based on the principle of data similarity.The results of experiments show that Dedup²can reduce the size of deduplication data set more than 50% effectively while maintain similar deduplication ratio.…”
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Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm by Ágota Bányai, Tamás Bányai, Béla Illés

“…Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. …”
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