Distribution of trust model in P2P network based on equilibrium theory

There are a large number of malicious attack nodes and collusion groups in P2P(peer to peer) network, and the existing trust models improve the P2P network environment to some extent, but the emphasis of the models are different, which are unable to fully solve large-scale malicious attacks and deception. Therefore, a P2P trust model based on equilibrium theory is presented. The model consists of the construction of the trust structure, the malicious node detection and trust speculation. It constructs trust network according to the equilibrium theory, uses the equilibrium theory to define nodes balance factor, detects balance malicious nodes by calculating the impact of malicious behavior on the network, and adopts trust inference algorithm to estimate trust nodes to prevent distrust network nodes being added. Experimental results show that the model is reliable, and the algorithm is efficient and robust.     

Trust management scheme based on community model for mobile Ad hoc networks

The security issues in mobile Ad hoc network, especially caused by inner malicious nodes are analyzed. By tracking the behavior of nodes, trust level of each node can be evaluated and managed; then actions of malicious nodes will be constrained and the security and reliability of entire network are enhanced. According to the features of Ad hoc. The scheme proposed in not only extends the conception of trust but also include the trust computation model and trust management mechanism. Simulation experiments show the novel scheme is more efficient than other trust schemes in traditional protocols.     

Game Analysis between Manufacturer and Wholesaler in the Management of Distribution Channel

In the distribution channel management, a good cooperation relationship between manufacture and wholesaler is an effective way for them to complement each other with their respective advantages, improve channel competitive abilities and adapt to market fluctuations. Based on their mutual cooperative relationship, a mixed game model is constituted by introducing the characteristics and postulating the prerequisites of trade between manufacturer and wholesaler, then the factors affecting their mutual cooperative relationship and the conditions of their stable cooperation are found through analyzing the mixed game model. Furthermore, a finitely repeated game model is used to analyze the cooperation between manufacturer and wholesaler, the conclusion of the cooperative qualification that influences the cooperation of both sides is given. As a result, the strategies employed by the manufacturer and wholesaler are pointed out.     

Compensation trust evaluation model of grid service

It is difficult to distinguish the cheating and other malicious behaviours in the grid service trust evaluation. A trust evaluation model for grid service based on compensation is proposed.With market mechanism, service provider and demander present the expected profit and compensate price for their behaviours to maximize their own profit. The game theory is applied to balance the expected profit and compensate price. Based on the game theory, evaluation trade strategy achieves perfect Bayesian equilibrium. Service provider and demander can choose their own trade strategy to maximize profit. Theoretical analysis and simulation results show that the service demanders can abandon the cheating motivation voluntarily, while the service providers can make right decision to choose trust evaluation. Compared with the existing model, the precision and security of the trust evaluation is enhanced greatly, while the calculating and communication cost is reduced remarkably.     

The optimal energy efficiency of wireless networks nodes based on solar cells

To improve the energy efficiency of solar cells in wireless sensor networks nodes, the energy relationship between solar cells and the wireless sensor networks nodes is studied. An adaptive algorithm is adopted to ensure the wireless sensor networks work normally at different sunlight intensities. An energy model is designed that reveals the energy relationship between the output power of the solar cells and the power of nodes working normally at a standard sunlight intensity. The experimental results show that the model represents the adaptive energy relationship between the solar cells and the nodes, ensures that the nodes work stably in a long term, and extends the life cycle of the sensor networks as long as possible. The model has important guiding significance for wireless sensor networks designation.     

大型商场建筑夏季冷负荷动态预测模型

夏季建筑冷负荷的正确预测是实现大型复杂中央空调优化运行、节能降耗的关键。笔者探讨了商场建筑冷负荷的主要影响因素,确定了建筑动态冷负荷预测模型的输入,提出了夏季基于新风机组供电频率的商场顾客率间接测量方法,解决了商场内顾客量难以检测的难题。还提出了AFC-HCMAC神经网络预测模型算法,实现了大型商场建筑冷负荷的动态预测。仿真结果表明:顾客率在商场冷负荷预测中占有重要地位,在冷负荷预测模型中增加商场顾客率可显著提高预测精度;AFC-HCMAC神经网络预测算法与传统的HCMAC神经网络算法比较,可有效降低神经网络节点数,提高预测精度。     

遗传算法的DV-Hop算法改进

DV-Hop算法中,平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差,对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离;然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离,减少平均每跳距离带来的误差。仿真结果表明,在不增加硬件开销的基础上,改进算法能够有效提高算法的定位精度,并且具有较好的稳定性。     

Research on the improvement of the convergencespeed for CDMA system power control

Optimal power control with game-theory has been a hot research topic in code division multiple access (CDMA) system. However, the convergence speed of the power control algorithm based on traditional static game-theory is not fast enough and the power fluctuation is large during the iterative process. In order to solve this problem, dynamic game-theory is introduced into CDMA system power control algorithm. The simulation results show that the proposed algorithm, compared with the distributed power control algorithm based on the traditional static game theory, can improve the convergence speed obviously with the same power spending.     

Improvement of Using Hash Table in Computer Bridge Double-dummy Solver

Incomplete information of the poker games make the research progress lags behind the chess games in AI. Although it is still very difficult to find a fast algorithm to solve a poker game with complete information which is the foundation of some advance researches. This paper gives a standard way to encode and store a game state into hash table, so the memory of hash table can be used more effectively and higher hit rate can be gotten in Scout search meth od. With the new encoding method, the total expanding leaf nodes reduces by around 5%.     

Optimal sensor deployment scheme for heterogeneous wireless sensor networks

For the high density of distributed heterogeneity nodes in wireless sensor networks (WSNs), the optimal sensor deployment is studied. A cost optimal heterogeneous sensor deployment scheme based on genetic algorithm is proposed. The cost of sensor node deployment is used as objective function for optimization computation subjected to network coverage and fault tolerance to obtain the suitable types and positions of the sensors. The algorithm can be used for boolean sensing model as well as probabilistic sensing model. The simulation results demonstrate that the proposed algorithm converges fast toward the optimal solutions and reduces the cost of sensor deployment, which is feasible for heterogenous nodes deployment in WSNs.     

An improved localization algorithm based on RSSI for landslide monitoring

In order to overcome the existing problems of low automation, high cost and difficult to implement in the area of landslide monitoring, this paper presents a new method of RSSI (Received Signal Strength Indicator)based positioning technology without any one-off instruments to monitor landslide surface displacement. By adding weighted factors, the improved positioning algorithm can estimate the parameters of the path loss model dynamically and calculates the communication distance of network nodes in real-time, which can improve positioning precision and reduce the impact of environmental changes on it. The MATLAB experiments show that, compared with the traditional RSSI based localization algorithm using fixed pass loss model, the improved algorithm could significantly reduce the average error.     

Analysis of Urban Reconstruction Based on Game Theory

The management of urban reconstruction is a process of game between the government and developers.It is helpful that the interest and its equilibrium for the relative parties involved in the reconstruction process are considered during the formation of government policy.This paper analyzes the environment for the policy constitution and establishes a model for strategy making based on the game theory.This model provides a basic foundation to improve the management ability of the government in the reconstruction process.Finally,in this paper some strategic issues are suggested to cope with the challenges from urban reconstruction in China.     

DHT的分层结构多出口选择问题研究

为了提高系统可靠性和查询效率,提出了具有多管理节点（出口节点）的DHT分层模型,并给出了3种查询算法：最短路径选择算法、基于热土豆模型的最小化组内流量算法和出口节点负载均衡选择算法。通过仿真实验对3种算法在查询效率、流量分析和负载均衡3个维度进行了分析比较,基于热土豆模型的最小化组内流量算法具有最高的查询效率,但是负载均衡性能最差,出口节点负载均衡选择算法具有最好的负载平衡性,但查询效率最低,最短路径算法性能则介于上述两种算法之间。同时对传统分层结构所采用的随机查询算法与基于热土豆模型的最小化组内流量和最短路径查询算法进行了性能对比。     

Improvement and performances of DV hop localization algorithm in wireless sensor networks

In order to improve the node localization precision of Range Free based DV Hop localization algorithm in wireless sensor networks (WSNs) with randomly distributed nodes and dynamic topology, the improved algorithm is proposed. After analyzing the DV Hop algorithm, considering the obvious errors of the estimated node coordinates calculated by Polygon based method in traditional DV Hop algorithm, the numerical iterative algorithm is constructed by employing Taylor series expansion, and simulation studies for the improved DV Hop algorithm are conducted. The selection criteria for the convergent threshold of iterative step is determined, the localization performance of the improved localization algorithm is analyzed by comparing with the traditional DV Hop algorithm under the same condition of selected convergent threshold and simulation parameters, while the calculation amount and convergence rate of the improved algorithm are also measured by the statistic iterations. The simulation results show that by selecting reasonable iterative threshold values and appropriately increasing calculation amount for node localization, the improved DV Hop localization algorithm greatly improves the localization precision and the error stability, which is feasible for node localization in WSNs with both randomly distributed nodes and dynamic topology.     

食品供需网可追溯体系构建的博弈分析

为突出食品供需网(FSDN)理念在可追溯体系构建上的优势,论文构建了食品供应链的Nash博弈均衡模型与食品供需网的Pareto博弈均衡模型,分析2种情况下企业构建食品可追溯体系的投入水平。结果发现在食品供应链中,企业在政策、法规等强制约束下会对可追溯体系的构建有一定的投入,但是投入水平较低。在食品供需网中,由Pareto均衡模型得出,企业对可追溯体系构建的投入高于Nash均衡水平。因此,食品供需网的构建可提高企业可追溯体系构建的投入水平,促使企业主动参与可追溯体系的构建和实施。     

Analysis of the Effect of Industrial Difference on the Level of Cooperation

The models of static game and repeated game in which industrial difference is considered are built. The degree of the industrial difference's effects on the level of optimal cooperation and the change of other factor's effect on the level of the optimal cooperation with the change of the industrial difference are analyzed. Some profound results on cooperation are obtained. These results are momentous current significance to explaining some recent economic behavior of Chinese enterprise and leading them to further deepen reform.     

A RELIABILTY CAPACITY OPTIMIZATION ALGORITHM FOR STOCHASTIC FLOW NETWORKS

A model and a heuristic algorithm for reliabilty op timi zation in generalized stochastic flow networks are proposed in this paper. The stochastic characteristic of the demands at terminal nodes is considered in the model. The algorithm proposed is powerful and can be applied to optimal planning of transmission capacity for large scale stochastic flow networks, because it can facilitate a fast location of optimal capacity expansion from the information obtained by the last iteration by making full use of the relationships of the k-weak link set and failure events set to the paramsters in generalized stochastic flow networks     

包含双边金融期权的农村电价古诺模型研究

打破电力市场垄断,提高农村电力市场效率,以及抑制市场力滥用是当今农村电力市场改革的主要方向之一。本文基于非合作博弈理论,提出了一种含买卖双边金融期权的、按照古诺竞争模式在现货市场和期权市场进行2阶段博弈的模型。由多家独立发电商与惟一的电网公司首先在期权市场中签订双边合同,决策出各自售出的最优期权数量;之后在现货市场进行产量竞争,在各自拥有期权头寸已知的情况下,选择其发电出力使自身期望收益最大。利用反向推倒方法求解模型,分析了模型中不同参数的变化对市场均衡结果的影响。通过理论研究和算例分析证明,与现有模型相比较,本文提出的含双边金融期权模型能够更大程度上降低市场出清价格以及提高发电量,可为电力监管机构与市场决策者引导参与者有序竞争提供一种新思路。     

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.     

联合局部和全局稀疏表示的磁共振图像重建方法

针对在压缩传感中独立使用全局或局部稀疏字典所分别导致的图像细节或整体图像结构信息的丢失,提出了一种联合利用局部和全局稀疏约束来捕捉磁共振图像细节和整体结构信息的磁共振图像重建算法。该算法首先从特定的磁共振图像中训练出稀疏字典,然后利用该字典进行局部稀疏编码。其次,利用预定义的全局字典来加强磁共振图像的全局稀疏性。最后,在局部和全局稀疏的共同约束下,利用非线性共轭梯度算法来对重建模型进行求解。整个重建过程可以重复迭代以逐步改善重建质量。实验结果表明：当下采样因子达到10时,相比于字典学习算法（dictionary learning MRI,DLMRI）,提出的算法在重建质量上可以提高1-6 dB。