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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 6 • Date Nov 2001

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Displaying Results 1 - 25 of 31
  • A model-based fuzzy logic controller with Kalman filtering for tracking mean arterial pressure

    Page(s): 676 - 686
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (235 KB) |  | HTML iconHTML  

    This paper proposes a new noninvasive measurement method for tracking the tendency of mean arterial pressure (MAP) in the radial artery. The designed system consists of a tonometer, a microsyringe device, and a model-based fuzzy logic controller. The modified flexible diaphragm tonometer is to detect the continuous blood pressure waveform and vessel volume pulse. A precise mathematical model describing the interaction between the tonometer and artery is derived. To reach accurate measurement without distortion, a model-based fuzzy logic control system is designed to compensate the change of MAP by applying a counter pressure on the tonometer chamber through the microsyringe device. The proposed control system consists of a linear predictor, a Kalman filter, and a synthetic fuzzy logic controller (SFLC). Simulation results show that, for the real physiologic MAP with changing rates up to 20 or -20 mm-Hg/minute, the model-based SFLC can beat-to-beat adjust the tonometer's chamber pressure to follow the tendency of MAP accurately View full abstract»

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  • A shelf-based Lagrangian relaxation algorithm to schedule parallelizable tasks

    Page(s): 687 - 697
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (337 KB) |  | HTML iconHTML  

    This paper generalizes classical scheduling theory by removing the restriction that only a single processor can work on a given task at a particular time. Instead, it is assumed that each task can be allocated any number of identical processors from one to the maximum number available, and that a task's completion time is a nonincreasing function of the number of processors allocated. Once started, a task must run to completion without altering the number of processors given to it. Furthermore, a task can start only when no task is currently executing. The objective considered is minimization of overall completion time (make-span) for the tasks subject to the constraint of a limited number of available processors. To approximately solve this problem, an algorithm based on Lagrangian relaxation is developed, and its performance is analyzed through extensive simulations. Approximate duality gaps range from 0 to about 60% on average and are strongly a function of problem type and size View full abstract»

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  • The minimum worst case error of fuzzy approximators

    Page(s): 714 - 716
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (85 KB) |  | HTML iconHTML  

    The approximation capability of fuzzy systems is an important topic of research when the systems are regarded as input-output maps. By using the notion of information-based complexity (IBC), we derive the minimum worst case error of a fuzzy approximator, which is independent of the detailed construction of the fuzzy rule bases View full abstract»

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  • Preference ratios in multiattribute evaluation (PRIME)-elicitation and decision procedures under incomplete information

    Page(s): 533 - 545
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (263 KB)  

    This paper presents the preference ratios in multiattribute evaluation (PRIME) method which supports the analysis of incomplete information in multiattribute weighting models. In PRIME, preference elicitation and synthesis is based on 1) the conversion of possibly imprecise ratio judgments into an imprecisely specified preference model, 2) the use of dominance structures and decision rules in deriving decision recommendations, and 3) the sequencing of the elicitation process into a series of elicitation tasks. This process may be continued until the most preferred alternative is identified or, alternatively, stopped with a decision recommendation if the decision maker is prepared to accept the possibility that the value of some other alternative is higher. An extensive simulation study on the computational properties of PRIME is presented. The method is illustrated with a re-analysis of an earlier case study on international oil tanker negotiations View full abstract»

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  • The power average operator

    Page(s): 724 - 731
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (251 KB) |  | HTML iconHTML  

    We introduce the power average to provide an aggregation operator which allows argument values to support each other in the aggregation process. The properties of this operator are described. We discuss the idea of a power median. We introduce some possible formulations for the support function used in the power average. We extend the supported aggregation facility of empowerment to a wider class of mean operators, such as the OWA (ordered weighted averaging) operator and the generalized mean operator View full abstract»

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  • Model reference robust speed control for induction-motor drive with time delay based on neural network

    Page(s): 746 - 753
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (244 KB)  

    Proposes a novel model-reference robust speed control with a load torque estimator and feedforward compensation based on a neural network (NN) for induction motor drives with time delay. First, a two-layer neural network torque estimator (NNTE) is used to provide real-time identification for an unknown load torque disturbance. The backpropagation algorithm was used as the learning algorithm. In order to guarantee the system's convergence and to obtain faster NN learning ability, a Lyapunov function is also employed to find the bounds of the learning rate. Since the performance of the closed-loop controlled induction motor drive is influenced greatly by the presence of the inherent system dead-time during a wide range of operations, a dead-time compensator (DTC) and a model-reference-following controller (MRFC) using a NN proportional controller (NNPC) are proposed to enhance the robustness of the PI controller. A theoretical analysis, simulation and experimental results all demonstrate that the proposed model-reference robust control scheme can improve the performance of an induction motor drive with time delay, and can reduce its sensitivity to system parameter variations and load torque disturbances View full abstract»

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  • TEMPER: a temporal programmer for time-sensitive control of discrete event systems

    Page(s): 485 - 496
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (218 KB) |  | HTML iconHTML  

    The paper is an extension of an earlier work (Zaidi, 1999) on a methodology for modeling temporal aspects of discrete-event systems. The methodology incorporates point and interval descriptions of time, and offers both qualitative and quantitative calculus for time. A graph-based temporal programmer (TEMPER) is shown to implement the axiomatic system of the temporal formalism. The approach transforms the system specifications given by temporal statements into a graph structure, identifies errors (if present) in the system, infers new temporal relations among system intervals, and calculates delays among time points and their actual time of occurrence View full abstract»

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  • Optimal approximation of linear systems by a differential evolution algorithm

    Page(s): 698 - 707
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    The problem of optimally approximating linear systems is solved by a differential evolution algorithm (DEA) incorporating a search-space expansion scheme. The optimal approximate rational model with/without a time delay for a system described by its rational or irrational transfer function is sought such that a frequency-domain L2-error criterion is minimized. The distinct feature of the proposed model approximation approach is that the search-space expansion scheme can enhance the possibility of converging to a global optimum in the DE search. This feature and the chosen frequency-domain error criterion make the proposed approach quite efficacious for optimally approximating unstable and/or nonmimimum-phase linear systems. The simplicity and robustness of the modified DEA in terms of easy implementation and minimum assumptions on search space are demonstrated by two numerical examples View full abstract»

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  • Searching for optimal trajectory with learning

    Page(s): 767 - 774
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    An algorithm of searching for the optimal trajectory with the minimal cost W(x) of reaching the final state xft n from the initial state x is presented. A system of ODEs is suggested to determine an optimal trajectory x*(t) and an optimal control u*(t). The trajectory x(t) and the control u(t) close to optimal ones are determined by successive approximations. The algorithm represents a development of a gradient method in the function space. Learning consists in estimation of an unknown a priori minimal cost W(x) and ∂W(x)/∂x on the basis of analysis of the trial trajectories x(t) obtained earlier View full abstract»

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  • Searching networks with unrestricted edge costs

    Page(s): 497 - 507
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (245 KB) |  | HTML iconHTML  

    Best-first and depth-first heuristic search algorithms often assume underlying search graphs with only nonnegative edge costs and attempt to optimize simple objective functions. Applicability of these algorithms to graphs with both positive and negative edge costs is not completely studied. In the paper, two new problems are identified: one in computational geometry and the other in the layout design of very large scale integrated (VLSI) circuits. The former problem relates to a weight-balanced bipartitioning of a given set of points in a plane. The goal of the second problem is to find an area-balanced staircase path in a VLSI floorplan. Formulations of these problems lead to an interesting directed acyclic search graph with positive, zero and negative edge costs and an objective function of general nature. These problems are NP-hard. To solve such general problems optimally, search schemes are proposed. Experimental results reveal the efficacy and versatility of the proposed schemes, the depth-first scheme being the better choice. It is shown that the classical number-partitioning problem can also be formulated in this framework View full abstract»

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  • Automating the analysis of option pricing algorithms through intelligent knowledge acquisition approaches

    Page(s): 573 - 586
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (347 KB) |  | HTML iconHTML  

    The traditional approach for estimating the performance of numerical methods is to combine an operation's count with an asymptotic error analysis. This analytic approach gives a general feel of the comparative efficiency of methods, but it rarely leads to very precise results. It is now recognized that accurate performance evaluation can be made only with actual measurements on working software. Given that such an approach requires an enormous amount of performance data related to actual measurements, the development of novel approaches and systems that intelligently and efficiently analyze these data is of great importance to scientists and engineers. The paper presents intelligent knowledge acquisition approaches and an integrated prototype system, which enables the automatic and systematic analysis of performance data. The system analyzes the performance data which is usually stored in a database with statistical, and inductive learning techniques and generates knowledge which can be incorporated in a knowledge base incrementally. We demonstrate the use of the system in the context of a case study, covering the analysis of numerical algorithms for the pricing of American vanilla options in a Black and Scholes modeling framework. We also present a qualitative and quantitative comparison of two techniques used for the automated knowledge acquisition phase View full abstract»

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  • Robust PI controller design for nonlinear systems via fuzzy modeling approach

    Page(s): 666 - 675
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (242 KB) |  | HTML iconHTML  

    The design problem of proportional and proportional-plus-integral (PI) controllers for nonlinear systems is studied. First, the Takagi-Sugeno (T-S) fuzzy model with parameter uncertainties is used to approximate the nonlinear systems. Then a numerically tractable algorithm based on the technique of iterative linear matrix inequalities is developed to design a proportional (static output feedback) controller for the robust stabilization of the system in T-S fuzzy model. Next, we transform the problem of PI controller design to that of proportional controller design for an augmented system and thus bring the solution of the former problem into the configuration of the developed algorithm. Finally, the proposed method is applied to the design of robust stabilizing controllers for the excitation control of power systems. Simulation results show that the transient stability can be improved by using a fuzzy PI controller when large faults appear in the system, compared to the conventional PI controller designed by using linearization method around the steady state View full abstract»

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  • Simulation-based policy generation using large-scale Markov decision processes

    Page(s): 609 - 622
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB)  

    This paper presents a new problem-solving approach, termed simulation-based policy generation (SPG), that is able to generate solutions to problems that may otherwise be computationally intractable. The SPG method uses a simulation of the original problem to create an approximating Markov decision process (MDP) model which is then solved via traditional MDP solution approaches. Since this approximating MDP is a fairly rich and robust sequential optimization model, solution policies can be created which represent an intelligent and structured search of the policy space. An important feature of the SPG approach is its adaptive nature, in that it uses the original simulation model to generate improved aggregation schemes, allowing the approach to be applied in situations where the underlying problem structure is largely unknown. In order to illustrate the performance of the SPG methodology, we apply it to a common but computationally complex problem of inventory control, and we briefly discuss its application to a large-scale telephone network routing problem View full abstract»

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  • Automated function generation of symptom parameters and application to fault diagnosis of machinery under variable operating conditions

    Page(s): 775 - 781
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (221 KB) |  | HTML iconHTML  

    Dimensional or nondimensional symptom parameters are usually used for condition monitoring of plant machinery. However, it is difficult to extract the most important symptom parameters and the functions of those parameters by which machinery faults can be sensitively detected and the fault types can be precisely distinguished. In order to overcome this difficulty and to ensure highly accurate fault diagnosis, a new method, called "automated function generation of symptom parameters" using genetic algorithms (GA) is presented in this paper. By applying the method to real machinery diagnosis problems, it has been shown that the key symptom parameter function can be quickly generated. We give a diagnosis example of rolling bearings whose operating conditions are variable in terms of rotation speed and load View full abstract»

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  • Feature representation and signal classification in fluorescence in-situ hybridization image analysis

    Page(s): 655 - 665
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (178 KB) |  | HTML iconHTML  

    Fast and accurate analysis of fluorescence in-situ hybridization images for signal counting will depend mainly upon two components: a classifier to discriminate between artifacts and valid signals of several fluorophores (colors), and well discriminating features to represent the signals. Our previous work (2001) has focused on the first component. To investigate the second component, we evaluate candidate feature sets by illustrating the probability density functions and scatter plots for the features. The analysis provides first insight into dependencies between features, indicates the relative importance of members of a feature set, and helps in identifying sources of potential classification errors. Class separability yielded by different feature subsets is evaluated using the accuracy of several neural network-based classification strategies, some of them hierarchical, as well as using a feature selection technique making use of a scatter criterion. Although applied to cytogenetics, the paper presents a comprehensive, unifying methodology of qualitative and quantitative evaluation of pattern feature representation essential for accurate image classification. This methodology is applicable to many other real-world pattern recognition problems View full abstract»

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  • High-speed customizable fuzzy-logic processor: architecture and implementation

    Page(s): 731 - 737
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (168 KB) |  | HTML iconHTML  

    A generic field-programmable logic device (FPLD)-based fuzzy logic system aimed at high-speed applications that can be easily customized for practically any application is presented. It implements fuzzy logic systems that vary in terms of the numbers of inputs and outputs and their accuracy, the membership functions (MFs), fuzzy rules, and the speed at which new outputs have to be generated. This is achieved by using the sysstem's unique architecture and its parameterized description, which is based on VHDL generics. The system can be used as either a stand-alone system or as an application-specific co-processor added to standard or customized microprocessors View full abstract»

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  • Team-Soar: a computational model for multilevel decision making

    Page(s): 708 - 714
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (162 KB) |  | HTML iconHTML  

    Computational models which symbolically represent the abstraction of reality on computers, have won popularity as research tools in organizational studies. However, very few, if any computational models have been used to test theories in the same ways that human experiments generally do. The author introduces a simulation experiment using a computational model of team called "Team-Soar," which mimics a human team experiment that was performed to test a theory of team decision making. The results support the major propositions of the multilevel theory in the same fashion as the ones of the human team experiment. The simulation experiment displays the Team-Soar model's effectiveness as a theory prover View full abstract»

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  • Virtual gravity and coupling control for robotic gait synthesis

    Page(s): 737 - 745
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB) |  | HTML iconHTML  

    In our previous works, we have proposed "virtual passive dynamic walking" with virtual gravity for biped robots in order to realize active walking on level ground without any gait design in advance. In this paper, we discuss some control problems of a kneed biped robot and propose "modified compass-like virtual passive dynamic walking" with active knee-lock algorithms in order to avoid the "foot scuffing" problem during the single support phase. Furthermore, a virtual coupling control law is proposed which can realize a variable walking pattern with respect to the robot's energy levels. By the effect of the control law, the robot, which is a hybrid dynamical system, can be regarded as a passive system which does not include any collisions, and a variable walking pattern can be realized without loss of the properties of a virtual passive walk. The validity of the proposed methods has been examined by numerical simulations View full abstract»

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  • New membership functions for effective design and implementation of fuzzy systems

    Page(s): 717 - 723
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (211 KB) |  | HTML iconHTML  

    The paper proposes new membership functions (mfs) for fuzzy modeling. Existing mfs do not simultaneously satisfy ease in optimization and low-end hardware implementation. The proposed mfs satisfy the two contradicting requirements. The algorithm for hardware implementation is detailed. The performance and applicability of the proposed mfs are illustrated using two well-known benchmarks. Optimized fuzzy models are coded and implemented using the Intel 8XC196KC microcontroller. Results show that the proposed mfs simplify offline design and facilitate online implementation View full abstract»

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  • A quasi-renewal process for software reliability and testing costs

    Page(s): 623 - 631
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (177 KB) |  | HTML iconHTML  

    This paper models software reliability and testing costs using a new tool: a quasi-renewal process. It is assumed that the cost of fixing a fault during software testing phase, consists of both deterministic and incremental random parts, increases as the number of faults removed increases. Several software reliability and cost models by means of quasi-renewal processes are derived in which successive error-free times are independent and increasing by a fraction. The maximum likelihood estimates of parameters associated with these models are provided. Based on the valuable properties of quasi-renewal processes, the expected software testing and debugging cost, number of remaining faults in the software, and mean error-free time after testing are obtained. A class of related optimization problem is then contemplated and optimum testing policies incorporating both reliability and cost measures are investigated. Finally, numerical examples are presented through a set of real testing data to illustrate the models results View full abstract»

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  • An intelligent system for failure detection and control in an autonomous underwater vehicle

    Page(s): 762 - 767
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (132 KB) |  | HTML iconHTML  

    Autonomous underwater vehicles (AUVs) have been used extensively in deep sea research. Failure detection and control is an important issue in maintaining the stability of an AUV. In most AUVs, the vehicle resurfaces in the event of minor failures such as in the depth sensor, the inclinometer, etc. The paper proposes an intelligent system for failure detection and control in AUVs where the vehicle could continue exploration in case of minor failures in the sensors and control surfaces. The intelligent system, based on the model proposed in Patel and Ranganathan (1996), integrates the adaptability of an artificial neural network (ANN) and the inferencing ability of a fuzzy rule based expert system on a single VLSI chip. The associative function of the ANN is used to recognize and detect the failures by observing the various changing parameters of the dynamic vehicle. The inferencing ability of an expert system suggests ways to control the failure and indicates the subsequent status of the vehicle. The entire system could be used as a low level diagnoser in an overall control system for AUVs View full abstract»

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  • Toward market-driven agents for electronic auction

    Page(s): 474 - 484
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (285 KB) |  | HTML iconHTML  

    While there are several existing agent-based systems addressing the crucial and difficult issues of automated negotiation and auction, this research has designed and engineered a society of trading agents with two distinguishing features: 1) a market-driven negotiation strategy and 2) a deal optimizing auction protocol. Unlike some of the existing systems where users manually select predefined trading strategies, in the market-driven approach, trading agents automatically select the appropriate strategies by examining the changing market situations. Results from a series of experiments suggest that the market-driven approach generally achieved more favorable outcomes as compared to the fixed strategy approach. Furthermore, it provides a more intuitive simulation of trading because trading agents are able to respond to different market situations with appropriate strategies. By augmenting the auction protocol with a deal optimization stage, trading agents can be programmed to optimize transaction deals by delaying the finalization of deals in search of better deals. Experimental results showed that by having a deal optimization stage, the auction protocol produced generally optimistic outcomes View full abstract»

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  • Estimation of number of people in crowded scenes using perspective transformation

    Page(s): 645 - 654
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB) |  | HTML iconHTML  

    In the past, the estimation of crowd density has become an important topic in the field of automatic surveillance systems. In this paper, the developed system goes one step further to estimate the number of people in crowded scenes in a complex background by using a single image. Therefore, more valuable information than crowd density can be obtained. There are two major steps in this system: recognition of the head-like contour and estimation of crowd size. First, the Haar wavelet transform is used to extract the featured area of the head-like contour, and then the support vector machine is used to classify these featured area as the contour of a head or not. Next, the perspective transforming technique of computer vision is used to estimate crowd size more accurately. Finally, a model world is constructed to test this proposed system and the system is also applied for real-world images View full abstract»

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  • Coordination of the supply chain of seasonal products

    Page(s): 524 - 532
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (174 KB)  

    Because of the demand uncertainty of seasonal products, the retailer prefers to place an order as late as possible, so that he can have enough time to collect more information, which is helpful to reduce demand forecast error. On the other hand, the manufacturer has limited production capacity in general cases. The late ordering would result in insufficient production times, thus increasing the production cost. Such a conflict exists universally in a supply chain, especially in the seasonal products' supply chain. As a result, coordination between the retailer and the manufacturer becomes very important. In the paper, based on the traditional operating system, an improved operating system is introduced whose impact to both bodies of a supply chain is examined under the condition of information symmetry. The result shows that the manufacturer may not be better off or well off, although the retailer's performance is improved. Then, some profit compensation plans are designed so as to make the operating system Pareto improve View full abstract»

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  • Formalized analysis of structural characteristics of large complex systems

    Page(s): 559 - 572
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (299 KB) |  | HTML iconHTML  

    Macrostructural modelization is paramount to the development of large complex systems (LCS). The paper explores the macrostructural modelization of LCS in terms of a block diagram based model and a grammar based model. Firstly, the macrostructural modelization problem of LCS is formulated. Secondly, a block diagram based model is proposed and established for LCS. Specifically, two general-purpose information-processing modules are proposed and constructed, called perception cube and decision spheroid. Thirdly, a grammar based model is proposed and established for LCS through applying formal language theory to the block diagram based model. Specifically, perception cube and decision spheroid are visually represented as context-free grammars, named fusion grammar and synthesis grammar, respectively. Through a stratified constructive linkup between a stream of bottom-up growing fusion grammars and a stream of top-down growing synthesis grammars, a level of LCS is constructively defined and accordingly represented as a context-free grammar, named level grammar. Then, a whole LCS is represented as a context-free grammar through a compounding of all level grammars. Finally, a case study is presented to demonstrate the potential usability of the proposed and established models of LCS View full abstract»

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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta