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In this paper, to solve the cooperative detection problem of ground observation for near space multi-sensor platform, put forward the index of multi-sensor platform optimal disposition, and the genetic algorithm is used to analysize the calculation process, finally, through an example shows the utility and value of the index and algorithms, implemented the optimal disposition of the multi-sensor platform.
Establishing high performance cooperation and estimating the nodes' risk in mobile ad hoc networks (MANETS) is currently fundamental and challenging due to the inherent characteristics of MANETS, such as highly dynamic topology and absence of an effective security mechanism. Trust based assessment methods were recently put forward but presumed restrictions to the data samples or presumed weights for...
It is well-known that wireless scheduling algorithm could exploit multi-user diversity to enhance the network capacity. With multiple transmit/receive antennas, there are additional degrees of freedom which could deliver either spatial multiplexing gain and/or spatial diversity gain. With cross layer scheduling, there is also multi-user selection diversity which contributes to both network capacity...
In this paper we consider the uplink of a cellular network partitioned into localized jointly decoded cells. These jointly decoded cells are implemented as fixed size clusters. Such networks have a potential for real world deployments with improved spectral efficiency and user experience. Similar to conventional cellular networks, frequency planning can be considered as an efficient method to control...
It is proposed in this paper a methodology to obtain optimal controllers gains for the rotor-side converter of doubly fed induction generators (DFIGs) using a genetic algorithm approach. The main objective is to enhance the operational security and robustness of the power system, by a more effective contribution of the DFIG controllers to the system controllability. To reach this goal, the crow-bar...
The primary goal of this paper is to save logistics cost and reach optimizing configuration of import crude oil transportation network. Firstly, based on the investigation of China's domestic oil production and consumption, this paper makes a detailed analysis on the source regions, flow, transportation routes and accommodating ports of import crude oil. Thereafter, an optimization model is put forward...
This paper explores website link structure considering websites as interconnected graphs and analyzing their features as a social network. Factor Analysis provides the statistical methodology to adequately extract the main website profiles in terms of their internal structure. However, due to the large number of indicators, a genetic search of their optimum number is proposed, and applied to a case...
Using genetic algorithm and BP neural network method of combining, this paper has established dynamic forward feedback correction model and has completed the automatic adjustment of the various parameters required for rolling steel pipe, and has made rolled steel pipe system work at the best value. After the actual data validation, the model can more accurately pre-adjusted parameters to achieve intelligent...
Computer games that handle realistic environments are becoming more popular in the game market. Games that make use of natural environments such as the spreading of fire or the flow of water need to be very carefully designed. In order to produce a desired effect of fire or water, a designer needs to try and test map properties several times. There has been an effort to use genetic algorithm to find...
In order to overcome the shortcomings of BP neural network, the golden section theory was used to get the reasonable number of Back Propagation (BP) neural network's hidden nodes. By using Genetic Algorithm (GA) to optimize the initial weights and threshold value of BP neural network, the network converged quickly and the recognition precision was increased. The GA-BP neural network model was utilized...
Although simple genetic algorithm (SGA) can, to some extent, improve the back propagation neural network (BP), it is prone to prematurity and losing the optimal solutions. Niche technology and fuzzy control theory are introduced to improve SGA and the improved one is used to optimize BP. The improved genetic algorithm is used to optimize BP neural network. In addition, due to the increasingly voltage...
This paper proposes an approach to find solution to the Bounded Knapsack Problem (BKP). BKP is a generalization of 0/1 knapsack problem in which multiple instances of distinct items but a single knapsack is considered. This problem occurs in many ways in real-life, such as cryptography, finance, etc. A genetic algorithm using greedy approach is proposed to solve this problem. The experiments prove...
Traffic flow prediction plays an important role in urban traffic management and control. Traditional prediction methods are mostly difficult to meet the high complexity, randomness and uncertainty characteristics of urban traffic flow. In this paper, a new prediction model is proposed based on self-adaptive neural network. Compared with other methods, it possesses the advantages of low computational...
The load balancing scheduling is the core of the load balancing technology in the cluster system. The actual load of servers will increase suddenly before the load value is updated if many clients link the servers in a short period. A mathematical model of load balancing was improved and an adaptive load balancing optimization scheduling based on genetic algorithm was proposed, analyzed and simulated...
Based on the deep research on Infrastructure as a Service (IaaS) cloud systems of open-source, we propose an optimized scheduling algorithm to achieve the optimization or sub-optimization for cloud scheduling problems. In this paper, we investigate the possibility to allocate the Virtual Machines (VMs) in a flexible way to permit the maximum usage of physical resources. We use an Improved Genetic...
The problem of end effects in Hilbert-Huang transform is produced in the Empirical Mode Decomposition (EMD), which has a badly effect on Hilbert-Huang transform. In order to overcome this problem, multi-objective Genetic Algorithm (GA) for solving the parameters selection of RBF Neural Network (RBF_NN) (GRHHT) is presented in this paper. Then the RBF_NN is used to predict the signal before EMD. The...
One of the most important issues for autonomous mobile robots is finding paths in their environment. A local path planner must be able to design the path immediately and if possible with high accuracy and efficiency. In this paper genetic algorithm is used in order to devise a path planner that reaches high accuracy like global path planners and at the same time with acceptable speed like local path...
Knapsack problem is a typical computer algorithm of NP complete (Nondeterministic Polynomial Completeness) problem. The research of solving this problem has great significance not only in theory, but also in application, for example, resource management, investment decisions and so on. For solving this problem, scholars have developed a number of algorithms, however, they are all have some drawbacks...
Air Combat Decision-Making for Coordinated Multiple Target Assignment is an important yet difficult problem in the modern information warfare. Previous methods, such as neural network, genetic algorithm, ant colony algorithm, particle swarm optimization and auction algorithm, used to resolve this problem have proved to be either too brittle or not stable. To address this problem, a new continuous...
A messy genetic algorithm (mGA), speculated by David Goldberg in 1989, is regarded as one of the most efficient method on those problems with Building Blocks (BB). While Hierarchical-if-and-only-if (HIFF) test problem is the basic example of a hierarchically consistent building-block problem. As it features hierarchical BB structure with multiple optima, HIFF test problem becomes the hardest test...
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