نتایج جستجو برای: swarm experience
تعداد نتایج: 415045 فیلتر نتایج به سال:
This paper proposes a novel approach of cross layer resource allocation based on Quality of Experience (QoE) for multiple applications in downlink Long Term Evolution (LTE) systems. To maximize the level of system QoE while guaranteeing the fairness for users, we introduce a Particle Swarm Optimization (PSO) based resource block allocation algorithm which has a quicker convergence rate. It is m...
The tail of the particle swarm optimisation (PSO) position distribution at stagnation is shown to be describable by a power law. This tail fattening is attributed to particle bursting on all length scales. The origin of the power law is concluded to lie in multiplicative randomness, previously encountered in the study of first-order stochastic difference equations, and generalised here to secon...
In this paper a new technique, named Function “Stretching”, for the alleviation of the local minima problem is proposed. The main feature of this technique is the usage of a two–stage transformation of the objective function to eliminate local minima, while preserving the global ones. Experiments indicate that combined with the Particle Swarm Optimizer method, the new algorithm is capable of es...
Previous work has demonstrated the feasibility of using process-oriented programming to implement simple subsumption architectures for robot control. However, the utility and scalability of process-based subsumption architectures for more complex tasks and those involving multiple robots has not been proven. We report our experience of applying these techniques to the implementation of a standa...
Pultrusion is one of several manufacturing processes for reinforced polymer composites. In this process fibers are continuously pulled through a resin bath and, after impregnation, the fiber-resin assembly is cured in a heated forming die. In order to obtain a polymeric composite with good properties (high and uniform degree of cure) and a process with a minimum of wasted energy, an optimizatio...
The particle swarm optimization technique is one of the promising tools to find a proper optimum for an unknown function optimization. Especially, global search capability of the method is very powerful. The particle swarm optimization utilizes common knowledge of the group and individual experiences effectively. That is, direction for the best estimator that a particle has ever reached, direct...
The loss of population diversity is one of main reasons which lead standard particle swarm optimization (SPSO) to suffer from the premature convergence when solving complex multimodal problems. In SPSO, the personal experience and sharing experience are processed with a completely random strategy. It is still an unsolved problem whether the completely random processing strategy is good for main...
This chapter steps back from specific self-organisational architectural solutions to consider what self-organisation means in the context of complex systems. Drawing on insights in complexity and selforganisation, the chapter explores how the natural propensity of complex systems (such as the mammalian immune system) to self-organise could be exploited as a mechanism for adaptation in complex c...
In this paper a new technique, named Function “Stretching”, for the alleviation of the local minima problem is proposed. The main feature of this technique is the usage of a two–stage transformation of the objective function to eliminate local minima, while preserving the global ones. Experiments indicate that combined with the Particle Swarm Optimizer method, the new algorithm is capable of es...
We describe simple simulation models of collective swarm behaviour of simple robots. We have experimented with mixed avoidance and seeking behaviour using triwheeled robots using simple ultrasonic proximity sensors. Our model assumes a radial distance of attraction or repulsion and supports multiple species in the swarm based on sensor recognition protocols. We describe the surprising success o...
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