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In this paper, we propose a two-stage thermal-aware task scheduling policy which exploits the application and system architecture characteristics to decouple the mapping of task-graphs for the performance and peak temperature optimization into two stages. At the first stage, the algorithm collects the best mapping of task-graphs exploiting the application and architecture characteristics to minimize...
This paper, in order to reduce fault and improve ratio of recognition, build adaptive neural network-based fuzzy inference system (ANFIS), which was applied to build a fault diagnosis model of automobile engine, adopts the method of information fusion in entropy method to optimize the input interface. To reduce the impact of excessive parameters on classification accuracy and cost, it also raises...
In order to solve the problem that the parameters of cloud model are difficult to get and the weight of performance index is difficult to obtain when adopt single objective optimization algorithm. A new design of cloud model controller based on multi-objective optimization is proposed. In the first stage, set the system overshoot, settling time, and ITAE index as the optimization objectives, then...
The fuzzy rule-based genetic algorithm (fuzzy-MOGA) is proposed in the paper to solve the problem of multi-objective optimization. The original chromosomes are generated with heuristic information. The Pareto optimal solutions are built by the arena's principle on the partial order set, so that it is easy to search the non-convex solution and it dos not need to determine weight value any more, which...
The location optimization model which is by established wireless sensor networks is a multi-objective and multi-constrained non-linear equation; and genetic algorithm as a evolutionary algorithm, it has merit of simple condition in application, strong ability in search capability, and particularly suitable for multi-objective, multi-binding solution, so it is very suitable for wireless sensor network...
The spanning tree-based genetic algorithm (ST-GA) is an effective method to solve the multi-objective transportation optimization problem. The performance of this algorithm is definitely superior to the typical matrix-based GA. A new fuzzy-GA is proposed in this paper. At first, it adopts the Pareto method, so that the problem that the non-convex solutions are difficult to be found through common...
In most sensor network applications, the information gathered by sensors will be meaningless without the location of the sensor nodes. Node localization has been a topic of active research in recent years. Accurate self-localization capability is highly desirable in wireless sensor network. A fundamental problem in distance-based sensor network localization is whether a given sensor network is uniquely...
The problem of minimum cost is studied aiming to the network structures. Firstly, the chance constrained model of optimum network structures is given. Then the solution strategy of ant colonies algorithm with random simulated and mutation operator is studied, and the detailed steps of hybrid intelligence is given. At last, an instance is given, optimum network structures of minimum cost which have...
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