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Table of Content

    31 August 2015, Volume 49 Issue 08 Previous Issue    Next Issue
    Automation Technique, Computer Technology
    An Attribute Similarity Adjusting Algorithm Based on Functional Dependency
    TAN Mingchaoa,DIAO Xingchuna,CAO Jianjuna,FENG Jingb
    2015, 49 (08):  1075-1083. 
    Abstract ( 652 )   Save

    Abstract: The accuracy of attribute similarity is one of the important factors affecting the precision of entity resolution (ER). To improve the accuracy of attribute similarity, the relation between attribute similarity and functional dependency (FD) was analyzed and the principles for attribute similarity adjusting were suggested. The FD based methods for similarity partition, similarity transitively adjusting and cost computing of similarity adjusting were proposed. An algorithm for attribute similarity adjusting with FD (SAWFD) was put forward to improve the accuracy of attribute similarity. The experiment results show that the algorithm can better distinguish matching and unmatching records, and get higher scores of recall, precision and F1 measure.

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    Expressiveness of WellStructured Pushdown Systems
    JIN Yang,CAI Xiaojuan,LI Guoqiang
    2015, 49 (08):  1084-1089. 
    Abstract ( 867 )   Save

    Abstract: A well-structured pushdown system(WSPDS) is a pushdown system equipped with well-quasi-order states and a well-quasi-order stack alphabet. It is shown that several extensions of vector addition systems can be reduced to a WSPDS. By applying post-order calculation of its derivation tree, the branching vector addition system can be encoded to some WSPDS. The recursive vector addtion system is a special class of WSPDS if a stack is explicitly introduced to its transitions. The vector addtion system with one zero-test can be encoded to some WSPDS where the depth of the stack represents the dimension for zerotest. These results exhibit the powerful expressivenss of WSPDS.

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    Design of a Fractional Order PID Controller for HighOrder Process with Inverse Response
    ZHAO Zhicheng,WANG Huifang,ZHANG Jinggang
    2015, 49 (08):  1090-1095. 
    Abstract ( 860 )   Save

    Abstract: A method for designing fractional order (FO) PID controller for the high-order process with inverse response was proposed in this paper.  In order to easily design the controllers, the model of high-order process was simplified using a modified particle swarm optimization (PSO) algorithm. Based on the simplified model, a fractional order PID controller was designed according to the principle of internal model control (IMC). Since the controller has only one adjustable parameter, the complexity of the controller tuning is effectively reduced. According to the maximum sensitivity index, the analytical expressions of the controller parameter tuning was deduced, and the blindness of selecting the parameters was overcome. The simulation results show that this method can enable the system to have good set-point tracking, disturbance rejection characteristics and robustness against the parameter perturbation of system.

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    Radiao Electronics, Telecommunication Technology
    Designing of a Fast Demodulation Method for Surface Acoustic Wave Torque Sensor
    FAN Yanping,JI Xiaojun,CAI Ping
    2015, 49 (08):  1096-1100. 
    Abstract ( 810 )   Save

    Abstract: To decrease the processing time and reduce the system complexity of surface acoustic wave(SAW) torque sensor, a fast timedomain demodulation method based on the frequency response characteristic of SAW resonator was designed. The SAW response characteristic was analyzed, and a signal truncation and denoising method were designed. The period of received was obtained by finding zero cross points. The operational frequency band was found according to the relation between the higher frequency and the period of the received signal. The resonant frequency of SAW sensor was obtained by estimating the spectrum of the signal with the maximum period. The proposed method acquires only one channel signal which reduces the complexity of the hardware system of SAW interrogator. The processing periods are completed in the timedomain which simplifies the demodulation algorithm. For a single scanning cycle, the executing time is appoximately 521 ms for the proposed method while that of the traditional method is 828 ms, which verifies the proposed method.

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    Automation Technique, Computer Technology
    Optimal Order-Replacement Policy for a Deteriorating System Based on Delayed Geometric Process
    CHENG Guoqing1,2,ZHOU Binghai1,LI Ling2
    2015, 49 (08):  1101-1107. 
    Abstract ( 655 )   Save

    Abstract: An orderreplacement model was developed for a repairable deteriorating system. The policy N was adopted where the system would be replaced after the the Nth failure and the spare system was ordered at the end of the (N-1)th failure. The deterioration process of the system was modeled by the delayed geometric process. The longrun average availability and the average cost rate were derived by using the renewal reward theory. The optimal policy was obtained under the premise of meeting the availability requirement. Finally, a numerical example was given to illustrate the proposed model.

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    Agent Control Technology for Hybrid Electric Vehicle Multi-Energy Powertrain
    NIU Limin,YE Lijun,RUAN Xiaodong
    2015, 49 (08):  1108-1113. 
    Abstract ( 771 )   Save

    Abstract: A multi-agent coordinated control method for hybrid electric vehicle (HEV) powertrain was proposed to improve the intelligent control, fuel economy and power performance of HEV. Taking the parallel HEV as prototype, agent models of parts subsystem were set up, and coordinated control framework of multiagent system was constructed. Pre-matching of assembly power was conducted according to different drive cycles. The adaptive problem of complex road condition was resolved by using intelligent active of single agent and cooperation ability of multi-agent. Simulation verification was carried out based on Cruise. The result shows that the multi-agent coordinated control strategy is valid and feasible. The HEV adapts its control model according to different drive cycles, further improving the vehicle fuel economy and power performance.

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    A Novel Algorithm for Collision Detection Based on Octree of Adaptive Subdivision and Encoding
    BAO Yidong1, 2,WU Dongmei1
    2015, 49 (08):  1114-1122. 
    Abstract ( 1020 )   Save

    Abstract: A novel algorithm for collision detection in robot operation training system based on octree of adaptive subdivision and encoding algorithm was proposed in this paper. Using this method, this structure can not only guarantee the real-time, and has the good topology. This octree structure adopts three times of the average triangle of the axis aligned bounding box to set the cell size. It is reasonable and effective compared with the radius of sphere. Based on the triangle size and the optimal cell size, by using the adaptive triangular mesh subdivision and the centroid distance, the collision in the space was detected. The experimental simulation data verify the realtime and effectiveness of the method.

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    Extraction of Product Service System Configuration Rules Based on Multi-objective DPSO Algorithm
    LIU Yuan1,ZHANG Zaifang1,YAO Di2,CHU Xuening3
    2015, 49 (08):  1123-1130. 
    Abstract ( 785 )   Save

    Abstract: To assist engineers to map customer requirements into technical characteristics of product service system effectively, a kind of rule extraction method combining DPSO with Pareto was proposed. The method includes establishing the model of product service system configuration rules and constructing the model of ParetoDPSO. In ParetoDPSO, continuous particle was mapped into a decimal discrete space using the frequency initialization method based on Sobol sequence and the particle discrete update method; Pareto was used to obtain the optimal set of rules by evaluating multiple target functions. By comparing with OMOPSO and DPSO, the feasibility and validity of the proposed method was verified by applying in the example of automotive product service system configuration design.

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    Evaluation of Network-Level Traffic State Using 2DLNMF Algorithm
    XU Rong,WU Cong,JIANG ShiZheng,CHEN QiMei
    2015, 49 (08):  1131-1136. 
    Abstract ( 747 )   Save

    Abstract: Network-level traffic state reflects the macroscopical conditions of the road network. The exesting evaluation algorithms have some shortcomings such as their applicable conditions are limited to section and they just depend on a single index. As a result, based on the analysis of the correlation between the measuring index and sections and the local nonnegative matrix factorization(LNMF) algorithm,  the algorithm of 2DLNMF was proposed and the features of the traffic data were extracted by choosing appropriate parameters to reduce the numbers of dimensions of the road network data. The simulation results indicate that the evaluation of 2DLNMF is more accurate and its online accuracy is up to 95.69%.

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    An Accurate and Robust Online Sequential Learning Algorithm for Feedforward Networks
    LU Chengbo,MEI Ying
    2015, 49 (08):  1137-1143. 
    Abstract ( 876 )   Save

    Abstract: In this paper, a kind of accurate and robust online sequential learning algorithm was proposed for single hidden layer feedforward networks. The algorithm is referred to as online sequential discrete Fourier transformextreme learning machine (OSDFTELM). This approach is able to learn data onebyone or chunkbychunk. During the growth of the data, input weights and output weights are adjusted incrementally. The proposed algorithm has a higher degree of accuracy and robustness compared to the approach referred to as online sequentialextreme learning machine (OSELM). Two simulation examples were presented to show the excellent performance of the proposed approach.

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    Network Security Situation Awareness Method Based on Multi-Source and Multi-Level Information Fusion
    WEN Zhicheng1,2,CHEN Zhigang1,DENG Xiaoheng1,LIU Anfeng1
    2015, 49 (08):  1144-1152. 
    Abstract ( 1015 )   Save

    Abstract: A comprehensive overall network security situation awareness framework was proposed, fully considering mul-information sources and multilevel information fusion, which can dynamically produce the current network security situation from the three dimensions, accurately reflect the current network security situation, and easily find the abnormal component. Besides,  a “3σ rule” to discretize continuous random variable was proposed that can establish a Bayesian network suitable for dealing with uncertain information fusion, providing important guidance to theory and practice. Making full use of network instance data, the model and algorithm are verified and the results show that the method is correct.

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    Online Semi-Supervised Extreme Learning Machine Based on Manifold Regularization
    WANG Ping,WANG Di,FENG Wei
    2015, 49 (08):  1153-1158. 
    Abstract ( 1296 )   Save

    Abstract: In this paper, with the help of the rules of block matrix multiplication, an online semi-supervised extreme learning machine(OSSELM) was proposed according to semi-supervised extreme learning machine (SS-ELM)  based on manifold regularization.By the analysis of the manifoldregularization term of the objective function of SSELM, a kind of approximation algorithm of OSS-ELM named OSS-ELM(buffer) was proposed to avoid running out of memory in the process of online learning.The linear relationship between the sample number and the cumulative running time of the OSS-ELM(buffer) was revealed in the experiments using Abalone and the relative deviation of the generalization ability of the OSSELM and the SS-ELM is less than 1% in 9 public data sets, which show that the OSSELM(buffer) not only solves the problem of limited memory, but also improves the speed of online learning while keeping the generalization ability of SSELM. This proves that the OSSELM(buffer)can be effectively applied to online semisupervised learning.

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    Lane Detection and Steering Control of Vision-Based Micro-Intelligent Vehicle
    WANG Jin,ZHAO Rui,CAO Baolin,DENG Xin,CHEN Qiaosong
    2015, 49 (08):  1159-1167. 
    Abstract ( 870 )   Save

    Abstract: To study the autonomous driving behaviour of intelligent vehicles, a visual navigationbased microintelligent vehicle system was proposed and implemented in this paper. The frame of the proposed system was introduced from the aspects of the hardware/software architecture and the data communication scheme. The performance of the traditional lane detection method is very limited in the microroad traffic environment with illumination variations. In the proposed approach, a gray scale morphology tophat transformation and brightness profile scanbased lane detection method was introduced to conquer this problem. To analyze the autonomous driving behaviour of intelligent vehicles in the smallscale traffic environment, a fuzzybased steering control algorithm was designed for simulating the behaviour of drivers. The experimental results show that the proposed scheme is able to effectively simulate the autonomous driving behaviour of vehicles in the real environment, and provides a new approach for the research of intelligent transportation system.

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    Nonrandom Community Detection Algorithm Based on Label Propagation
    LIU Gongshen,ZHANG Haolin,MENG Kui,SU Bo
    2015, 49 (08):  1168-1173. 
    Abstract ( 679 )   Save

    Abstract: The advantages of classical community detection algorithm based on label propagation include precision and time complexity. On the other hand, there are several disadvantages, such as oscillation, unstable result, tendency of big community. The nonrandom community detection algorithm based on label propagation (NCDAL) proposed by this paper improves the disadvantages of the classical algorithm by getting rid of its random procedures. There are three improvements in the NCDAL: when renewing the label, there is the special order; when summing up the labels, both current vertex and its neighbors are counted; and when selecting the label, the contribution function is defined to avoid random selection. It is approved by the experiments that the proposed algorithm not only has high precision, but also decreases random procedures of the classical algorithm.

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    Analysis and Calculation of Feasible Region of Multi-Robot Combined Lifting System
    ZHAO Zhigang1,TENG Fujun1,SHI Guangtian1,LI Jinsong2,JI Gang2
    2015, 49 (08):  1174-1180. 
    Abstract ( 719 )   Save

    Abstract: A closedloop kinematic chain composed of multirobots and used to tow a common object was presented and the feasible regions including the position feasible region and the posture feasible region were defined. Based on the given system structure and the relationship displacement and velocity constrain, the position and posture kinematics models of the system were built, and the dynamic model of the system was established. Based on object position and posture, the feasible regions of position and posture were analyzed, and a method  to solve the  feasible regions of position and posture of the system by Mentocarlo algorithm was given. Finally, under the given parameters conditions, the feasible regions of position and posture of the system by numerical calculation method were obtained, which will lay a solid foundation for future research of trajectory planning, path tracking, and stability of the system.

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    Optimization Design of FaultTolerant Image Filter
    Based on Genetic Algorithm
    BAO Zhiguo,WAN Jinliang,MA Xifeng
    2015, 49 (08):  1181-1185. 
    Abstract ( 690 )   Save

    Abstract: Aiming at the problem that there may be some fault units in a reconfigurable logic arrays, and using the genetic algorithm to evolve image filter for the logic array, the correctness of the results, the circuit speed, power consumption and complexity were taken into consideration. Experimental results show that when there is less fault logic module in the arrays, filter circuit can be generated whose function is close to the arrays with no fault.

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    An Active Disturbance Rejection Controller Based on Inverse Hyperbolic Sine Function
    ZHOU Tao
    2015, 49 (08):  1186-1190. 
    Abstract ( 973 )   Save

    Abstract: A third-order tracking differentiator and a third-order extended state observer (ESO) with an inverse hyperbolic sine function were proposed in this paper. The control law was designed with this function and the second-order derivative of the desired input signal. A new active disturbance rejection controller(ADRC) was constructed. Moreover, the asymptotic stability at the equilibrium point of the ADRC system was proved with the Lyapunov function. Finally, the simulation experiments demonstrate that the ADRC second-order system can track the square wave signal and sine signal in higher precision by rejecting the inner and outer nonlinear disturbance, and the ESO can accurately estimate the inner and outer disturbance.
     

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    A MultiObjective Integrated Optimization Method for FJSP Based on Multi-Rule Resource Allocation
    GAO Li1a,2,ZHOU Binghai2,YANG Xueliang1b,Wang Jixia1a
    2015, 49 (08):  1191-1198. 
    Abstract ( 849 )   Save

    Abstract: In order to reduce the complexity of multi-objective optimization in flexible jobshop scheduling and improve optimization efficiency, a multiobjective integrated optimization method with multiple resource constraints was proposed in this paper. Firstly, an integrated optimization model was established according to the objectives of minimum completion time, optimal human resource allocation plan, maximum equipment load and lowest production costs. Besides, in  view of the explosive characteristics of combination model,  an integrated scheduling rule for multiple resources allocation was presented to reduce the model complexity. As for the selection strategies of the scheduling rules, the rules with a high probability were preferentially selected through adjusting the probability of rules. In addition, the multiplerule guiding mechanism was adopted to push the search process toward the target direction. Furthermore,  the improved nondominated sorting genetic algorithm (NSGAⅡ) was adopted to obtain the Pareto solution sets of different probability values of the rules. Finally, the effectiveness of the proposed method was verified by simulation comparison.

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    Video Anomaly Detection Based on Statistic Feature of Optical Flow Block
    YU Haoa,SUN Tanfenga,b,JIANG Xinghaoa,b
    2015, 49 (08):  1199-1204. 
    Abstract ( 872 )   Save

    Abstract: An anomaly detection algorithm based on the statistic feature of optical flow block was proposed. First, the whole optical flow field of training video sequences were obtained. Then, each optical flow field was divided into blocks and each block was preprocessed in order to extract the statistic feature considering both magnitude and phase information of the block. The Gaussian mixture model (GMM) was employed  to establish the probability model of normal behaviors by feeding the statistic feature into it. The abnormal degree of the optical flow block was judged by the output posterior probability of the GMM probabilistic model. The experimental results show that the method proposed considers both the consistency information of moving objects and the partial occlusion issue, at the same time, improves the accuracy of anomaly detection.

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    Radiao Electronics, Telecommunication Technology
    Adaptive Impairment-Aware Routing and Wavelength Assignment Algorithm Based on MultiParameters Constraint
    XIONG Yu1,2,ZOU Xuan1,FAN Xue1,ZHANG Ruoying1
    2015, 49 (08):  1205-1212. 
    Abstract ( 680 )   Save

    Abstract: In order to effectively solve the problem of the signal quality degradation caused by the physical layer impairments in the transparent optical networks, the RWA algorithm of adaptive impairmentaware routing and wavelength assignment based on multiparameters constraint was proposed. According to the current state of the network in the process of routing, the weights of the physical layer multiconstraint parameters were adjusted dynamically to select the optimal light path. Meanwhile, the wavelength ordering problem was converted into finding the shortest Hamilton circuit in wavelength assignment, by utilizing an offline integer linear programming model to search the optimal wavelength order. Taking linear and nonlinear physical layer impairments into consideration in both the routing and wavelength assignment process, the quality of transmission can be ensured. The simulation results show that the proposed algorithm can reduce the blocking probability of the network, improving the blocking caused by the quality of light paths.

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    Automation Technique, Computer Technology
    Human Object Tracking Algorithm for Human-Robot Interaction
    ZHANG Tie,MA Qiongxiong
    2015, 49 (08):  1213-1219. 
    Abstract ( 1058 )   Save

    Abstract: Proposed in this paper is a human object tracking algorithm for HRI (Humanrobot interaction) as a solution to the interference by similar human objects when a robot is tracking a specified human object. In the proposed algorithm, all interference regions are regarded as candidate targets, and a particle distribution model based on overlapping rate is established to make particles converge to all candidate targets via a mean shift with a reduced number. Then, by taking the total error of weight distance and the target size as the clustering conditions, particles are divided into corresponding candidate target particles, and the best candidate target is selected as the tracking result. The experimental results show that the proposed algorithm can track targets accurately in the presence of surrounding similar objects, and  it possesses strong robustness and good realtime performance.

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    Communication and Transportation
    A Novel Swarm Intelligence Optimization Algorithm for Solving Constrained Multimodal Transportation Planning
    LIANG Xiaolei,LI Wenfeng,ZAHNG Yu
    2015, 49 (08):  1220-1229. 
    Abstract ( 733 )   Save

    Abstract: In order to apply the swarm intelligence (SI) algorithms effectively to solve the multimodal transportation planning problem, this paper proposed a decoding strategy to build a mapping modal between individual representation of SI and multimodal transportation schedule. In the modal, a method for traffic assignment in a multimodal transportation network was provided to decode each individual to an initial schedule. Then, a strategy for local traffic adjustment was applied to mend these initial schedules to improve the success rate of decoding. A developed particle swarm optimization (PSO) algorithm was also proposed to solve the planning problem compared with three other stateofart swarm intelligence optimization algorithms. A novel way that applies social network evolution behavior to adjust the swarm topology and individuals’ neighborhood and promote the interaction modal among individuals was introduced in the proposed algorithm. The numerical test of an operational problem shows that the decoding strategy is efficient in solving the multimodal transportation planning problem and the proposed algorithm has a superior performance on the terms of convergence speed and solution accuracy in comparison with the selected algorithms.

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    Problems and Development Mechanism of Smart City Delivery from Standardization Perspective
    LIU ShiLin1,MA Na1,2,ZHAO Siyu1
    2015, 49 (08):  1231-1236. 
    Abstract ( 749 )   Save

    Abstract: Under the circumstance of irreversible urbanization, smart city has been paid great attention to and promoted as the type of city in the future. Problems have emerged regarding the external expression of imbalance between intelligence and wisdom, such as technology superposition, replacing demand with function, resource waste and repeated construction, and internal friction of city operation. Based on the anatomy of the essence and the crucial points of smart cities, this paper lays out a developing mechanism for smart cities, and emphasizes some important aspects at the same time, including respecting city characteristics, paying close attention to interconnection and interoperation, and defining the future direction of a smart city according to public perception. Furthermore, suggestions to accelerate smart city development with the help of standardization are provided.

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    Others
    Customer-Oriented Group Buying Strategy in DualChannel Supply Chain
    XIAO Xiao,LUO Jianwen
    2015, 49 (08):  1237-1243. 
    Abstract ( 759 )   Save

    Abstract: The effect of group buying strategies in different sales channels on optimal supply chain decision was analyzed under two decisionmaking approaches in a dualchannel supply chain where the manufacturer sells goods to the ultimate consumers through traditional retail channel as well as direct online channel. The research shows that under centralized system, initiating group buying through the channel with larger market share will benefit the whole supply chain, while under decentralized system, in contrast, initiating group buying through the direct online channel has the same effect on the whole supply chain. However, the retail channel will decrease not only the optimal scale of group buying but also the increment of the overall benefit of the supply chain. Finally, a numerical analysis was given to testify the conclusion.
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    Analysis of Two-Period News-Vendor Problems with Service-Level Constraints
    LIU Bin,DONG Ming,ZHANG Dali
    2015, 49 (08):  1244-1248. 
    Abstract ( 771 )   Save

    Abstract: This paper discussed the single buyer’s optimal purchasing decision in two-period when facing opportunity constraints of service level. By constructing a model, the optimal ordering policy and the analytical solution to the optimal objective value were proposed. Numerical analysis was conducted of the parameters in the model. Meanwhile, a comparison was made between the proposed model and the single period newsvendor problem with service level constrain in the literature. Finally, the impacts of the variation of parameters of these two models on optimal objective value and solution were analyzed.
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    Incentive Mechanism for Cooperation in Evolution of Game Behaviors on Complex Networks
    XIE Fengjie
    2015, 49 (08):  1256-1262. 
    Abstract ( 971 )   Save

    Abstract: The evolution of cooperation behaviors in the prisoner’s dilemma game on complex networks depends on the sufficient cooperators in the initial state. By introducing the incentive mechanism of human social organizations, this paper studied the evolution of cooperative behaviors in the prisoner’s dilemma game while a small amount cooperators exist in the initial state, and focus on the effect of incentive on the evolution of cooperative behaviors under the network structures constrains. First, an incentive condition on square lattice was theoretically analyzed. Under that condition, a single cooperator on square lattice can evolve to form the clusters of cooperators. Then, by using simulation, the effects of incentive mechanism on the evolution of cooperative behaviors were explored while a small amount of initial cooperators were randomly distributed on square lattice, regular small world network and heterogeneous network, respectively. The results show that incentive mechanism facilitates the evolution of cooperative behaviors in general. But on the square lattice and regular small world network, the incentive mechanism sometimes does not necessarily correspond to better cooperation status, and even has negative effect. These results have important inspiration on management practice.
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