this paper describes a micro-scale sputter ion pump and its use in the controlled reduction of pressure in a large cavity package. the pump is composed of titanium electrodes on a glass substrate which are sputtered a...
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this paper presents the application of an evolutionary neural network controller in a stabilisation problem involving an inverted pendulum. It is guaranteed that the resulting closed-loop discrete system is asymptotic...
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ISBN:
(纸本)3540354530
this paper presents the application of an evolutionary neural network controller in a stabilisation problem involving an inverted pendulum. It is guaranteed that the resulting closed-loop discrete system is asymptotically stable. the process of training the neural network controller can be treated as a constrained optimisation problem where the equality constraint is derived from the Lyapunov stability criteria. the decision variables in this investigation are made up from the connection weights in the neural network, a positive definite matrix required for the Lyapunov function and matrices for the stability constraint while the objective value is calculated from the closed-loop system performance. the optimisation technique chosen for the task is a variant of genetic algorithms called a cooperative coevolutionary genetic algorithm (CCGA). Two control strategies are explored: model-reference control and optimal control. In the model-reference control, the simulation results indicate that the tracking performance of the system stabilised by the evolutionary neural network is superior to that controlled by a neural network, which is trained via a neural network emulator. In addition, the system stabilised by the evolutionary neural network requires the energy in the level which is comparable to that found in the system that uses a linear quadratic regulator in optimal control. this confirms the usefulness of the CCGA in nonlinear discrete system stabilisation applications.
In this paper a multi-period inventory lot sizing scenario, where there are multiple products and multiple suppliers, is solved with a Real Parameter Genetic Algorithm. We assume that demand of multiple discrete produ...
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ISBN:
(纸本)3540354530
In this paper a multi-period inventory lot sizing scenario, where there are multiple products and multiple suppliers, is solved with a Real Parameter Genetic Algorithm. We assume that demand of multiple discrete products is known, not exactly, over a planning horizon and transaction cost is supplier dependent, but does not depend on the variety nor quantity of products involved and holding cost is product-dependent and there are no capacity restrictions and no backlogging is allowed. Because of uncertainties in demand and inventory costs, we consider demand and all costs as fuzzy numbers. the problem is formulated as a fuzzy mixed integer programming and then converted to equivalent crisp decision making problems and is solved with a Real Parameter Genetic Algorithm. Finally, numerical example is provided to illustrate the solution procedure. the results determine what products to order in what quantities with which suppliers in which periods.
the organizational structure of the police is characterized by the existence of a centralized command withthe task of distributing and redistributing the police force in a region according to an analysis of crime and...
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Pervasive surveillance implies the continuous tracking of multiple targets as they move about the monitored region. the tasks to be performed by a surveillance system are expressed as the following requirements:(1) Au...
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the process of coalition formation, where distinct autonomous agents come together to act as a coherent group is an important form of interaction in multi-agent systems. Previous work has focused on developing coaliti...
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We present a profile based meta-reasoning model for parameter control of CAD algorithms working under constrained run-time. We also propose a unified framework, that can take informed decision about the time allocatio...
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We present a profile based meta-reasoning model for parameter control of CAD algorithms working under constrained run-time. We also propose a unified framework, that can take informed decision about the time allocation and parameter adaptation of the algorithm, where there is no hard run-time constraints, instead the quality-time tradeoff is expressed by a utility function. We use the proposed strategy to get an adaptive cooling schedule for the simulated annealing algorithm. Application on two classical NP-hard problems in the VLSI domain, namely, the standard cell placement problem and the circuit partitioning problem shows that significant improvement of quality can be achieved using a profile based control.
this volume presents proceedings from the 19th IFIP World computer Congress in Santiago, Chile. the proceedings of the World computer Congress are a product of the gathering of 2,000 delegates from more than 70 countr...
ISBN:
(数字)9780387348315
ISBN:
(纸本)9780387348285
this volume presents proceedings from the 19th IFIP World computer Congress in Santiago, Chile. the proceedings of the World computer Congress are a product of the gathering of 2,000 delegates from more than 70 countries to discuss a myriad of topics in the ICT domain. Of particular note, this marks the first time that a World computer Congress has been held in a Latin American country. Topics in this series include: - the 4thinternationalconference on theoretical computerscience - Education for the 21st Century- Impact of ICT and Digital Resources - Mobile and Wireless Communication Networks - Ad-Hoc Networking - Network control and Engineering for QoS, Security, and Mobility - the Past and Future of Information systems: 1976-2006 and Beyond - History of Computing and Education - Biologically Inspired Cooperative Computing - Artificial Intelligence in theory and Practice - Applications in Artificial Intelligence - Advanced Software Engineering: Expanding the Frontiers of Software
High-level synthesis compilers often produce reoccurring patterns in intermediate CDFGs during translation. By identifying large reoccurring patterns, one may reduce area and communication overhead by efficiently reus...
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High-level synthesis compilers often produce reoccurring patterns in intermediate CDFGs during translation. By identifying large reoccurring patterns, one may reduce area and communication overhead by efficiently reusing hardware for multiple operations. this paper presents an algorithm for dynamically generating templates of reoccurring patterns for resource sharing in CDFGs. Results show 40-80% resource reduction using small, incremental template growth, and variations within a 5% margin among varying look-ahead depths.
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