MODIS Aerosol Optical Thickness Product Algorithm Verification and Analysis by Yulong He, Lin Sun, Zhendong Sun, Xueqian Hu

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Adaptive Array Beamforming Using a Chaotic Beamforming Algorithm by Ana Jovanović, Luka Lazović, Vesna Rubežić

“…The Chaotic beamforming adaptive algorithm is new adaptive method for antenna array’s radiation pattern synthesis. …”
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Multi-objective task offloading algorithm for mobile cloud computing by Fuhong SONG, Huanlai XING, Wei PAN

Subjects: “…multi-objective evolutionary algorithm…”
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Enhancing the Classical Closed-Loop Algorithm in terms of Power Consumption by Rahman Mirzaei, Seyed Sina Kourehli

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An Improved PSO Algorithm for Distributed Localization in Wireless Sensor Networks by Dan Li, Xian bin Wen

“…Simulation results indicate that the proposed distributed localization algorithm is superior to the previous algorithms.…”
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Opportunistic spectrum access algorithm based on cross-layer optimization by ZHANG Jing, ZHU Hong-bo

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Guess and determine attack on E₀algorithm by Ying-jie ZHAN, Lin DING, Jie GUAN

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PRESEE: An MDL/MML Algorithm to Time-Series Stream Segmenting by Kaikuo Xu, Yexi Jiang, Mingjie Tang, Changan Yuan, Changjie Tang

“…Moreover, the performance of these algorithms depends heavily on parameters, which are hard for the users to set. …”
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SL-n iterative localization algorithm in wireless sensor networks by LUO Xu, CHAI Li, YANG Jun

“…To compensate for the lackness of robustness caused by MMSE（minimum mean square estimation） in overall situation in wireless sensor network iterative multilateration algorithm,a new estimation algorithm called SL-n were proposed.Firstly all samples were obtained using trilateration or partial MMSE from every combination of n reference nodes which belonged to some blind node,then the location of the blind node were estimated.Simulation experiments show that the proposed SL-n algorithm outperforms MMSE method in overall situation and can reduce the position error sufficiently when the reference error is large.…”
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MIMO-Based Forward-Looking SAR Imaging Algorithm and Simulation by Ziqiang Meng, Yachao Li, Shengqi Zhu, Yinghui Quan, Mengdao Xing, Zheng Bao

“…Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.…”
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Asymptotic RZF cooperative beamforming algorithm based on energy efficiency by Yinghui ZHANG, Biao ZHANG, Xiaoting LU, Yang LIU

“…A low complexity asymptotic regularized zero forcing cooperative beamforming algorithm based on energy efficiency in heterogeneous massive MIMO system was proposed,aiming at the problem that the current multi-flow regularization zero forcing beamforming algorithm sets the power constraint of each antenna in the regularization term as a fixed value and ignores the influences of factors such as the number of antennas,the number of users and QoS.The algorithm selects the optimal antenna power constraint set through the optimization method,and the optimal beamforming was asymptotically ob-tained to balance the interference among users to achieve the optimal energy efficiency,considering the impact of the number of antennas and users with the constraints of the antenna power and QoS.In view of the importance of backhaul in massive MIMO system,a backhaul power consumption model and the impact of backhaul power consumption on system performance was analyzed.Analysis and simulation results show that the proposed algorithm has great improvement of the performance,especially when the number of antennas is large.The algorithm is close to optimal performance,especially suitable for massive MIMO system of next generation communication.…”
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Energy-efficient object tracking algorithm in wireless sensor networks by REN Qian-qian1, LI Jian-zhong1, LI Jin-bao2, ZHU Jing-hua1

“…An energy efficient tracking algorithm（EETA） was proposed,which reduced energy consumption in sensor network by introducing an event-driven sleep scheduling mechanism.EETA gave tradeoffs between real time and energy efficiency by letting a maximum number of sensor nodes outside tracing area stay asleep,and reduced the computation complexity to O（N） by formulating the location predication of an object as a state estimation problem of sensor node,in-stead of building a complex model of its trajectory.Meanwhile,EETA located the object by using adaptive weighted cen-troid algorithm with complexity of O（N）.The method was evaluated with a network of 64 sensor nodes,as well as an analytical probabilistic model.The results demonstrate the effectiveness of the method.…”
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A regional augmented PPP algorithm for offshore considering NWP by Ying Xu, Xiangdan Meng, Jianhui Cui, Lin Ma

“…Meanwhile, almost all stations can achieve a faster solution convergence by this algorithm. Furthermore, the algorithm is suitable not only for areas that lack reference stations at sea but also for the lack of reference stations on land.…”
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Network selection algorithm based on synergetic for heterogeneous wireless network by Ran LUO, Su ZHAO, Qi ZHU

“…A network selection algorithm based on synergetic for heterogeneous wireless network was proposed. …”
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Network scheduling algorithm based on Stackelberg Game with incentive strategy by WEI Jiao-long, HU Jin, DAI Wen-juan, ZOU Jia-hong

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Efficient i-DFA construction algorithm based on state grouping by Deng-ke QIAO, Qing WANG, Ting-wen LIU, Yong SUN, Li GUO

“…Regular expression matching plays an important role in many network and security applications.DFA is the preferred representation to perform regular expression matching in high-speed network,because of its high and stable matching efficiency.However,DFA may experience state explosion,and thus consume huge memory space.As a classical solution for the problem of state explosion,i-DFA can reduce the memory consumption significantly and guarantee the worst matching performance at the same time.However,prior methods are inefficient in both time and space during the construction of i-DFA.An efficient i-DFA construction algorithm based on the idea of state grouping was proposed.Furthermore,a formal description for the problem of state grouping was given,and it was proved that it was NP-hard to get the best state grouping result.Thus,based on local search strategy,a near-optimal algorithm was introduced to divide states into different groups.Compared with the classical construction method,the significant improvement in both time and space is achieved; the i-DFA of the proposed method may have 2/3 states as that of prior method and the proposed i-DFA is constructed with only 1/16 time of it.…”
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Self-learning differential evolution algorithm for dynamic polycentric problems by Xing-bao LIU, Jian-ping YIN, Chun-hua HU, Rong-yuan CHEN

“…A novel self-learning differential evolution algorithm is proposed to solve dynamical multi-center optimization problems.The approach of re-evaluating some specific individuals is used to monitor environmental changes.The proposed self-learning operator guides the evolutionary group to a new environment,meanwhile maintains the stable topology structure of group to maintain the current evolutionary trend.A neighborhood search mechanism and a random immigrant mechanism are adapted to make a tradeoff between algorithmic convergence and population diversity.The experiment studies on a periodic dynamic function set suits are done,and the comparisons with peer algorithms show that the self-learning differential algorithm outperforms other algorithms in term of convergence and adaptability under dynamical environment.…”
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Risk Assessment of Government Debt Based on Machine Learning Algorithm by Dan Chen

“…This paper builds an effective government debt risk assessment system based on machine learning algorithm. According to forming the performance of local government debt risk and its internal and external influencing factors, this study applies the analytic hierarchy process, entropy method, and BP neural network method to construct the local government risk assessment index system, which includes the primary and secondary indexes including the explicit debt risk, the contingent implicit debt risk, and the financial and economic operation risk. …”
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Eliminating Network Depth: Genetic Algorithm for Parameter Optimization in CNNs by M. Askari, S. Soleimani, M. H. Shakoor, M. Momeni

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A　Genetic　Algorithm　for　Routing　in　Packet-Switched　Communication　Networks by He Cuihong Ou Yishan Li Xianji (Guangdong Institute of Technology, Guangzhou 510090)

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