This paper establishes the model which aims at inspection and maintenance issue as to the deteriorating system during discrete state and continuous time by the Semi-Markov Decision Process. Due to the probability conc...
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ISBN:
(纸本)9787894631046
This paper establishes the model which aims at inspection and maintenance issue as to the deteriorating system during discrete state and continuous time by the Semi-Markov Decision Process. Due to the probability concerning state transition is difficult to derived, in addition to escape local optimal result, a algorithm which combines the concept of Q-learning and simulated annealing is proposed in this article to get the optimal maintenance policy. Finally we obtain the optimized result in both average and discount criteria, and the simulation result indicates the feasibility of this method. Furthermore, the paper discusses the influence of inspection interval on the optimized average cost by the emulational data, which is in accordance with the fact.
An improved particle swarm optimization (IPSO) with oscillating inertia weight factor and self-adaptation mutation factor is proposed in this paper. The IPSO algorithm is used to achieve the partition of information s...
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The traditional hierachical reinforcement learning methods is used to solve multi-Agent system, which based on discrete time multi-Agent semi-Markov decision process with discount criteria, which cannot apply to conti...
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ISBN:
(纸本)9787894631046
The traditional hierachical reinforcement learning methods is used to solve multi-Agent system, which based on discrete time multi-Agent semi-Markov decision process with discount criteria, which cannot apply to continuous time multi-Agent infinite tasks. Therefore, in this paper, we introduce a kind of continuous time multi-Agent hierarchical reinforcement learning model, and propose an Option algorithm that applies to average or discounts criteria. The algorithm is under the framework of continuous time multi-Agent semi-Markov decision process, and it introduces a method of macro action communication that between agents on the top, which can solve a wide class of continuing tasks of continuous time multi-Agent. Finally, this proposed hierarchical reinforcement learning optimization algorithm is tested in a multi-Agent robotic garbage collection system, and the experimental results show that it needs less memory, and has a better optimization performance and faster learning speed than a multi-Agent continuous time Option algorithm, which use joint stat and joint macro action on the top.
Simulation studies of Doppler ultrasound blood flow signals from intracranial aneurysms in a pulsatile flow can provide a useful guidance for detecting the formation and growth progress of the intracranial aneurysms u...
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ISBN:
(纸本)9781424458219;9781424458240
Simulation studies of Doppler ultrasound blood flow signals from intracranial aneurysms in a pulsatile flow can provide a useful guidance for detecting the formation and growth progress of the intracranial aneurysms using the Doppler ultrasound technology and forecasting the size of aneurysm. Firstly, blood flow velocity distribution in the area of Intracranial aneurysm is calculated by solving the Navier-Stokes equations. Secondly, power spectral density (PSD) of the Doppler signals is estimated by summing the contribution of all scatterers through the vessel radius divided into elemental radius. Finally, the Doppler ultrasound blood flow signals are simulated using the cosine summation method. The model generates Doppler blood flow signals with the characteristics similar to those found in practice. The results show that the proposed approach is useful for simulating Doppler ultrasound signals from intracranial aneurysms in a pulsatile flow.
Two identification models are obtained for multivariable ARX systems by different parameterization, and the corresponding two least squares and two stochastic gradient algorithms are given based on the lest squares pr...
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Two identification models are obtained for multivariable ARX systems by different parameterization, and the corresponding two least squares and two stochastic gradient algorithms are given based on the lest squares principle and the stochastic gradient search principle and minimizing different cost functions. The performances of these algorithms are analyzed and compared by the simulation tests.
From perspective of objectivity of trust, a group Trust model which is used to depict constraint relationships among individuals in a particular group through covering four basic constraint patterns and their nesting;...
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From perspective of objectivity of trust, a group Trust model which is used to depict constraint relationships among individuals in a particular group through covering four basic constraint patterns and their nesting; what's more, gauging methods of direct trust degree and recommendation trust degree of basic constraint patterns and their nesting are brought up based on Bayesian method, and these methods remarkably support group trust relationship, especially trust relationship of software groups. Analysis on expressive power and validity of group Trust model proves that this model has outstanding adaptability and practicability.
In order to follow the development of image interpretation and data-processing system in photoelectric measurement equipments, a kind of hardware acceleration system is designed where MIMD distributed multi-processor ...
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In order to follow the development of image interpretation and data-processing system in photoelectric measurement equipments, a kind of hardware acceleration system is designed where MIMD distributed multi-processor architecture is used with SOPC technology. System hardware is composed of FPGA, SDRAM, SRAM, FLASH, and PCI bridge chip. Four Nios II embedded processors are integrated in a single FPGA chip, and communicate with each other by sharing memory. Experimental results indicate that the system meets the requirements of data-processing system in photoelectric measurement equipments and possesses practical significance for engineering applications.
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