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Computer Modeling and Simulation, 2008. EMS '08. Second UKSIM European Symposium on

Date 8-10 Sept. 2008

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Displaying Results 1 - 25 of 111
  • [Front cover]

    Publication Year: 2008 , Page(s): C1
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  • [Title page i]

    Publication Year: 2008 , Page(s): i
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  • [Title page iii]

    Publication Year: 2008 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2008 , Page(s): iv
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  • Table of contents

    Publication Year: 2008 , Page(s): v - xii
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  • Chair's Welcome Message

    Publication Year: 2008 , Page(s): xii
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  • Organization

    Publication Year: 2008 , Page(s): xiii - xv
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  • Sponsors

    Publication Year: 2008 , Page(s): xvi
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  • Trends in Discrete Event Simulations

    Publication Year: 2008 , Page(s): 1
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (717 KB) |  | HTML iconHTML  

    Discrete event simulation technologies have been up and down as global manufacturing industries went through radical changes. The changes have created new problems, challenges and opportunities to the discrete event simulation. On manufacturing applications, it is no longer an isolated model but the distributed modeling and simulation along the supply chain. In order to study the hybrid manufacturing systems, it is critical to have capability to model human performance with different level of skills and under various working conditions. On service applications, the most critical part is to model knowledge workers and their decision making process. The speaker reviews the discrete event simulation technologies; discusses challenges and opportunities presented by both global manufacturing and the knowledge economy. View full abstract»

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  • Advances in High-Speed Real-Time Simulation

    Publication Year: 2008 , Page(s): 2 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (119 KB) |  | HTML iconHTML  

    The demands of modern applications for ever increasing performance for real-time simulations have posed considerable challenges to simulation developers which are still not fully met. An effective response to these challenges has involved an interesting combination of a return to old-style programming techniques such as multi-rate simulation and low-level program design with a focus on individual machine cycles, with new technologies (DSP, FPGA, cell architecture) and algorithms (state transition, QSS). Some of these possibilities remain to be explored and the prospects for future research are very encouraging. View full abstract»

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  • Modelling and Optimisation of Reheat Furnace

    Publication Year: 2008 , Page(s): 9 - 14
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB) |  | HTML iconHTML  

    Some problems are known to have computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs portfolio of intelligent systems algorithms for optimising a metal reheat furnace scheduling problem. The proposed system has been evaluated for different techniques of the reheat furnace scheduling problem. Different optimisation methods have been used, namely: particle swarm optimisation (PSO), genetic algorithm (GA) with different classic and advanced versions: GA with chromosome differentiation (GACD), age GA (AGA), and sexual GA (SGA), and finally a mimetic GA (MGA), which is based on combining the GA as a global optimiser and the PSO as a local optimiser. Simulations have been performed to evaluate the systempsilas performance. View full abstract»

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  • Fuzzy Model for Decision Taking of Technologies in Home and Building Electronic Systems

    Publication Year: 2008 , Page(s): 15 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1208 KB) |  | HTML iconHTML  

    Many systems of automation, energy management, and security for housings and buildings exist nowadays, and the determination of the most appropriate one depends on multiple factors. This work, based on a previous analysis, presents a fuzzy model that allows evaluating these different systems in order to choose automatically one of them. The model considers the most outstanding factors for the selection as input variables of a fuzzy model, where the output variables measure the grade of adaptation of every system. A high number of rules are defined to develop the inference and generate the output values, and these outputs are analysed depending on pairs of inputs, in order to know their sensitivity. The proposed model is developed with the fuzzy logic toolbox of MATLAB, and is evaluated on ten different cases, which are presented in order to show the methodology, the behaviour of the model and the results. View full abstract»

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  • Stability Analysis and Parameter Selection of a Particle Swarm Optimizer in a Dynamic Environment

    Publication Year: 2008 , Page(s): 21 - 27
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (288 KB) |  | HTML iconHTML  

    The paper addresses the issues of parameter selection of a particle swarm optimization algorithm by a thorough stability analysis of the swarm dynamics. The effectiveness of the work lies in considering the dynamic behavior of the local and the global best particle positions, which usually are treated as constant in the existing analysis. The behavior of an individual particle here is modeled as a closed loop control system, represented by a signal flow graph. The stability analysis of the closed loop system is undertaken using Jury's test and root locus technique of classical control theory, and the result obtained from the analysis offers a more stringent condition on parameter selection in comparison to the existing results on stability analysis. Computer simulation of particle swarm algorithm further confirms better performance of the algorithm, when parameters are selected following the results of stability analysis. View full abstract»

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  • A Lyapunov-Based Extension to PSO Dynamics for Continuous Function Optimization

    Publication Year: 2008 , Page(s): 28 - 33
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (298 KB) |  | HTML iconHTML  

    The paper proposes three alternative extensions to the classical global-best particle swarm optimization dynamics, and compares their relative performance with the classical particle swarm optimization algorithm. The first extension, which readily follows from the well-known Lyapunov's stability theorem, provides a mathematical basis of the particle dynamics with a guaranteed convergence at an optimum. The inclusion of local and global attractors to this dynamics leads to faster convergence speed and better accuracy than the classical one. The second extension augments the velocity adaptation equation by a negative randomly weighted positional term of individual particle, while the third extension considers the negative positional term in place of the inertial term. Computer simulations further reveal that the last two extensions outperform both the classical and the first extension in convergence speed and accuracy. View full abstract»

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  • Model Parameters Optimisation for an Industrial Application: A Comparison between Traditional Approaches and Genetic Algorithms

    Publication Year: 2008 , Page(s): 34 - 39
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB) |  | HTML iconHTML  

    Model parameters optimisation is a very common problem when dealing with mathematical models. These models are often designed from theoretical considerations on the physics phenomena and afterwards adapted in order to fit the experimental data that are collected on the real operating scenario. The paper compares different approaches to the problem of finding the optimal values of four parameters characterising a quite complex mathematical model which estimates some important mechanical properties of aluminium killed and interstitial free steels. Several optimisation procedures have been attempted, from traditional methods to genetic algorithms. A comparison of such methods is performed, by illustrating and discussing numerical results. View full abstract»

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  • Vibration and Input Tracking Control of Flexible Manipulator Using LQR with Non-Collocated PID Controller

    Publication Year: 2008 , Page(s): 40 - 45
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (270 KB) |  | HTML iconHTML  

    This paper presents investigations into the development of control schemes for end-point vibration suppression and input tracking of a flexible manipulator. A constrained planar single-link flexible manipulator is considered and the dynamic model of the system is derived using the assumed mode method. To study the effectiveness of the controllers, initially a Linear Quadratic Regulator (LQR) is developed for control of rigid body motion. This is then extended to incorporate a non-collocated PID controller for control of vibration (flexible motion) of the system. Simulation results of the response of the manipulator with the controllers are presented in time and frequency domains. The performances of the control schemes are assessed in terms of level of vibration reduction, input tracking capability and time response specifications. Finally, a comparative assessment of the control techniques is presented and discussed. View full abstract»

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  • Modeling of Atmospheric Dispersion from Point Source

    Publication Year: 2008 , Page(s): 46 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    This paper deals with numerical approach to modeling of atmospheric dispersion of pollutant caused by a point source. The modeling of a pollution in the atmosphere has a long history and has gone throw great improvements over the last century. Two main methods can be distinguished from the modeling point of view: the analytical and the numerical methods. Both methods have their advantages and disadvantages, however, in the latest developments the numerical method has had the major role. Our work has been concerned on modeling pollution in the atmosphere caused by small sources. These sources can be marked as point sources. For the primary validation of our numerical solution, we have used a simple version of the model. The analytical solution of this version can be obtained and may be used for comparison. An intended progress of our work is outlined at the end of the paper. View full abstract»

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  • Noise Removal Using Hopfield Neural Network in Message Transmission Systems

    Publication Year: 2008 , Page(s): 52 - 57
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (146 KB) |  | HTML iconHTML  

    In this paper, a novel approach of two-tier encryption is proposed with the removal of noise generated during transmission based on Hopfield neural networks (HNN). The proposed system reduces the complexity of recognition of characters due to external distortion or diffusion. Though there are many error correction and detection codes, these codes request retransmission when there is an error. If the error rate is high the number of retransmissions are high which causes a delay in the process of communicating the information. Moreover the error correction systems can prevent the systems from data loss but will not help in recognition of letters if diffused. When HNN is added to the existing system, the learning ability enables the network to understand or even remember the pattern. But when images of larger size are stored, the network fails to recognize, which leads to further research in this area. View full abstract»

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  • Pareto Dominance-Based Approach for the Component Selection Problem

    Publication Year: 2008 , Page(s): 58 - 63
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (167 KB) |  | HTML iconHTML  

    Component selection is a crucial problem in component based software engineering (CBSE). CBSE is concerned with the assembly of pre-existing software components that leads to a software system that responds to client-specific requirements. We are approaching the component selection problem. We formulate the problem as multiobjective, involving 2 objectives: the number of used components and the cost of the involved components. We use the Pareto dominance principle to deal with the multiobjective optimization problem. The approach used is an evolutionary computation technique (a steady state evolutionary algorithm). The experiments and comparisons with greedy approach show the effectiveness of the proposed approach. View full abstract»

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  • Dynamic Channel Assignment Problem in Mobile Networks Using Particle Swarm Optimization

    Publication Year: 2008 , Page(s): 64 - 69
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (315 KB) |  | HTML iconHTML  

    The problem of optimal channel assignment has become increasingly important because of available frequency spectrum and increasing demand for cellular communication services. This has been shown to be an Np complete optimization problem. Many heuristic approaches including neural network, simulated annealing and genetic algorithm have been used to solve it. In this paper we propose a novel and efficient channel assignment approach, particle swarm optimization, to seek a conflict free channel assignment such that demand is achieved. Simulations on six well-known benchmark problems showed that the PSO could effectively generate the low-band results. View full abstract»

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  • A Multi-Objective Pareto-Optimal Solution to the Box-Pushing Problem by Mobile Robots

    Publication Year: 2008 , Page(s): 70 - 75
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (226 KB) |  | HTML iconHTML  

    The paper provides a new formulation of the well-known box-pushing problem by robots as a multi-objective optimization problem, and presents Pareto-optimal solutions to the problem. The proposed method allows both turning and translation of the box, while shifting it to a desired goal position. Local planning scheme is employed here to determine the magnitude of the forces applied by two mobile robots at specific locations on the box to align and translate it in each distinct step of motion of the box, so as to minimize the consumption of both time and energy. This is realized using non-dominated sorting genetic algorithm-II (NSGA-II). The proposed scheme, to the best of the authors' knowledge, is a first successful communication-free, centralized co-operation between two robots applied in box-shifting, satisfying multiple objectives simultaneously using evolutionary algorithm. View full abstract»

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  • An Evolutionary Algorithm for Uniform Parallel Machines Scheduling

    Publication Year: 2008 , Page(s): 76 - 80
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (295 KB) |  | HTML iconHTML  

    Scheduling problems are very important for many (research) fields. However only for few instances there are polynomial time optimization algorithms, because the vast majority of scheduling problem instances is NP-hard. In such cases heuristic and/or stochastic algorithm are used which tend toward but do not guarantee the finding of optimal solution. The aim of our paper is to investigate the performance of stochastic algorithms, i.e. genetic algorithm, in solving scheduling problems. We present the results obtained for two instances of Q| |Cmax scheduling problem. The obtained results were compared with results obtained by other optimization techniques, i.e. (another) genetic algorithm, simulated annealing, particle swarm optimization and multi-objective evolutionary algorithm. The comparison revealed that our genetic algorithm outperform the considered approaches because the results are very close (even equal) to the optimal solution. View full abstract»

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  • Glial Reservoir Computing

    Publication Year: 2008 , Page(s): 81 - 86
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    In trying to mimic biological functions of the brain, artificial neural network (ANN) research has, out of computational necessity, made a number of assumptions. Firstly, it is assumed that the complexity of biological processes can be usefully replicated artificially by abstracting a relatively few key or essential characteristics from the biological system. Secondly, it is often assumed that a single entity, the neuron, is solely responsible for biological cognitive processing or computation. Thirdly, it is also often assumed that this processing is entirely dependant on microscopic factors within the neuron. Recent research using spiking neural networks (SNNs) has addressed the first assumption, highlighting that emphasizing alternative biological functionality may afford massive computational gain. In an attempt to address the last two assumptions, the authors propose that the glial network may be acting as a feature extraction network in a way that is similar to the function of a reservoir computer. View full abstract»

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  • A Weighted Utility Framework for Mining Association Rules

    Publication Year: 2008 , Page(s): 87 - 92
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (306 KB) |  | HTML iconHTML  

    Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of occurrence in a record i.e. their weight and utility is the same (weight=1 and utility=1) which is not always the case. However, items are actually different in many aspects in a number of real applications such as retail marketing, nutritional pattern mining etc. These differences between items may have a strong impact on decision making in many application unlike the use of standard ARM. Our framework, weighted utility ARM (WUARM), considers the varied significance and different frequency values of individual items as their weights and utilities. Thus, weighted utility mining focuses on identifying the itemsets with weighted utilities higher than the user specified weighted utility threshold. We conduct experiments on synthetic and real data sets using standard ARM, weighted ARM and weighted utility ARM (WUARM) and present analysis of the results. View full abstract»

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  • Threat Modeling Revisited: Improving Expressiveness of Attack

    Publication Year: 2008 , Page(s): 93 - 98
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (908 KB) |  | HTML iconHTML  

    Threat modeling plays an important role in the deployment of optimal security controls and a number of threat modeling techniques have been proposed. However, most of the existing techniques lack adequate semantics and expressiveness. This paper reviews the existing techniques and proposes threat net; a technique based on information and causality theory concepts which offers improved expressiveness and semantics of threat models. Threat net is built on Petri nets and treats every node in the threat path as a random variable, whose values include time specific attacker profile and system defense capabilities. In theory, by computing the expected value of random events one can estimate the cost of achieving a given goal. We believe that the simplicity and richness of our technique will make it attractive to security experts. In future we hope to validate threat net using case-based analysis theory. View full abstract»

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