8 resultados para Hausdorff Metric

em Greenwich Academic Literature Archive - UK


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The performance of loadsharing algorithms for heterogeneous distributed systems is investigated by simulation. The systems considered are networks of workstations (nodes) which differ in processing power. Two parameters are proposed for characterising system heterogeneity, namely the variance and skew of the distribution of processing power among the network nodes. A variety of networks are investigated, with the same number of nodes and total processing power, but with the processing power distributed differently among the nodes. Two loadsharing algorithms are evaluated, at overall system loadings of 50% and 90%, using job response time as the performance metric. Comparison is made with the ideal situation of ‘perfect sharing’, where it is assumed that the communication delays are zero and that complete knowledge is available about job lengths and the loading at the different nodes, so that an arriving job can be sent to the node where it will be completed in the shortest time. The algorithms studied are based on those already in use for homogeneous networks, but were adapted to take account of system heterogeneity. Both algorithms take into account the differences in the processing powers of the nodes in their location policies, but differ in the extent to which they ‘discriminate’ against the slower nodes. It is seen that the relative performance of the two is strongly influenced by the system utilisation and the distribution of processing power among the nodes.

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In this paper, we discuss the problem of maintenance of a CBR system for retrieval of rotationally symmetric shapes. The special feature of this system is that similarity is derived primarily from graph matching algorithms. The special problem of such a system is that it does not operate on search indices that may be derived from single cases and then used for visualisation and principle component analyses. Rather, the system is built on a similarity metric defined directly over pairs of cases. The problems of efficiency, consistency, redundancy, completeness and correctness are discussed for such a system. Performance measures for the CBR system are given, and the results for trials of the system are presented. The competence of the current case-base is discussed, with reference to a representation of cases as points in an n-dimensional feature space, and a Gramian visualisation. A refinement of the case base is performed as a result of the competence analysis and the performance of the case-base before and after refinement is compared.

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This paper describes the architecture of the knowledge based system (KBS) component of Smartfire, a fire field modelling tool for use by members of the fire safety engineering community who are not expert in modelling techniques. The KBS captures the qualitative reasoning of an experienced modeller in the assessment of room geometries, so as to set up the important initial parameters of the problem. Fire modelling expertise is an example of geometric and spatial reasoning, which raises representational problems. The approach taken in this project is a qualitative representation of geometric room information based on Forbus’ concept of a metric diagram. This takes the form of a coarse grid, partitioning the domain in each of the three spatial dimensions. Inference over the representation is performed using a case-based reasoning (CBR) component. The CBR component stores example partitions with key set-up parameters; this paper concentrates on the key parameter of grid cell distribution.

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In this paper we propose a generalisation of the k-nearest neighbour (k-NN) retrieval method based on an error function using distance metrics in the solution and problem space. It is an interpolative method which is proposed to be effective for sparse case bases. The method applies equally to nominal, continuous and mixed domains, and does not depend upon an embedding n-dimensional space. In continuous Euclidean problem domains, the method is shown to be a generalisation of the Shepard's Interpolation method. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The performance of the retrieval method is examined with reference to the Iris classification problem,and to a simulated sparse nominal value test problem. The introducion of a solution-space metric is shown to out-perform conventional nearest neighbours methods on sparse case bases.

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In this paper we propose a case base reduction technique which uses a metric defined on the solution space. The technique utilises the Generalised Shepard Nearest Neighbour (GSNN) algorithm to estimate nominal or real valued solutions in case bases with solution space metrics. An overview of GSNN and a generalised reduction technique, which subsumes some existing decremental methods, such as the Shrink algorithm, are presented. The reduction technique is given for case bases in terms of a measure of the importance of each case to the predictive power of the case base. A trial test is performed on two case bases of different kinds, with several metrics proposed in the solution space. The tests show that GSNN can out-perform standard nearest neighbour methods on this set. Further test results show that a caseremoval order proposed based on a GSNN error function can produce a sparse case base with good predictive power.

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This paper describes the use of a blackboard architecture for building a hybrid case based reasoning (CBR) system. The Smartfire fire field modelling package has been built using this architecture and includes a CBR component. It allows the integration into the system of qualitative spatial reasoning knowledge from domain experts. The system can be used for the automatic set-up of fire field models. This enables fire safety practitioners who are not expert in modelling techniques to use a fire modelling tool. The paper discusses the integrating powers of the architecture, which is based on a common knowledge representation comprising a metric diagram and place vocabulary and mechanisms for adaptation and conflict resolution built on the Blackboard.

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Traditionally, when designing a ship the driving issues are seen to be powering, stability, strength and seakeeping. Issues related to ship operations and evolutions are investigated later in the design process, within the constraint of a fixed layout. This can result in operational inefficiencies and limitations, excessive crew numbers and potentially hazardous situations. University College London and the University of Greenwich are in the final year of a three year EPSRC funded research project to integrate the simulation of personnel movement into early stage ship design. This allows the assessment of onboard operations while the design is still amenable to change. The project brings together the University of Greenwich developed maritimeEXODUS personnel movement simulation software and the SURFCON implementation of the Design Building Block approach to early stage ship design, which originated with the UCL Ship Design Research team. Central to the success of this project is the definition of a suitable series of Naval Combatant Human Performance Metrics which can be used to assess the performance of the design in different operational scenarios. The paper outlines the progress made on deriving the human performance metric from human factors criteria measured in simulations and their incorporation into a Behavioural Matrix for analysis. It describes the production of a series of SURFCON ship designs based on the RN Type 22 Batch 3 frigate, and their analysis using the PARAMARINE and maritimeEXODUS software. Conclusions to date will be presented on the integration of personnel movement simulation into the preliminary ship design process.

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Traditionally, when designing a ship the driving issues are seen to be powering, stability, strength and seakeeping. Issues related to ship operations and evolutions are investigated later in the design process, within the constraint of a fixed layout. This can result in operational inefficiencies and limitations, excessive crew numbers and potentially hazardous situations. This paper summarises work by University College London and the University of Greenwich prior to the completion of a three year EPSRC funded research project to integrate the simulation of personnel movement into early stage ship design. This integration is intended to facilitate the assessment of onboard operations while the design is still highly amenable to change. The project brings together the University of Greenwich developed maritimeEXODUS personnel movement simulation software and the SURFCON implementation of the Design Building Block approach to early stage ship design, which originated with the UCL Ship Design Research team and has been implemented within the PARAMARINE ship design system produced by Graphics Research Corporation. Central to the success of this project is the definition of a suitable series of Performance Measures (PM) which can be used to assess the human performance of the design in different operational scenarios. The paper outlines the progress made on deriving the PM from human dynamics criteria measured in simulations and their incorporation into a Human Performance Metric (HPM) for analysis. It describes the production of a series of SURFCON ship designs, based on the Royal Navy’s Type 22 Batch 3 frigate, and their analysis using the PARAMARINE and maritimeEXODUS software. Conclusions on the work to date and for the remainder of the project are presented addressing the integration of personnel movement simulation into the preliminary ship design process.