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JournalISSN: 0020-7721

International Journal of Systems Science 

Taylor & Francis
About: International Journal of Systems Science is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Nonlinear system & Control theory. It has an ISSN identifier of 0020-7721. Over the lifetime, 8025 publications have been published receiving 109955 citations. The journal is also known as: Systems science.


Papers
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Journal ArticleDOI
TL;DR: The usual algebraic operations on real numbers are extended to fuzzy numbers by the use of a fuzzification principle, and the practical use of fuzzified operations is shown to be easy, requiring no more computation than when dealing with error intervals in classic tolerance analysis.
Abstract: A fuzzy number is a fuzzy subset of the real line whose highest membership values are clustered around a given real number called the mean value ; the membership function is monotonia on both sides of this mean value. In this paper, the usual algebraic operations on real numbers are extended to fuzzy numbers by the use of a fuzzification principle. The practical use of fuzzified operations is shown to be easy, requiring no more computation than when dealing with error intervals in classic tolerance analysis. The field of applications of this approach seems to be large, since it allows many known algorithms to be fitted to fuzzy data.

2,412 citations

Book ChapterDOI
TL;DR: Today, as a step towards the control of complex dynamic systems, models are being used ubiquitously, being modelled, for instance, are the air traffic flows around New York, the endocrine balances of the pregnant sheep, and the flows of money among the banking centres.
Abstract: Today, as a step towards the control of complex dynamic systems, models are being used ubiquitously. Being modelled, for instance, are the air traffic flows around New York, the endocrine balances of the pregnant sheep, and the flows of money among the banking centres.

1,017 citations

Journal ArticleDOI
TL;DR: A review and categorization of electric load forecasting techniques is presented, dividing them into nine categories: multiple regression, exponential smoothing, iterative reweighted least-squares, adaptive load forecasting, stochastic time series, ARMAX models based on genetic algorithms, fuzzy logic, neural networks, and expert systems.
Abstract: A review and categorization of electric load forecasting techniques is presented. A wide range of methodologies and models for forecasting are given in the literature. These techniques are classified here into nine categories: (1) multiple regression, (2) exponential smoothing, (3) iterative reweighted least-squares, (4) adaptive load forecasting, (5) stochastic time series, (6) ARMAX models based on genetic algorithms, (7) fuzzy logic, (8) neural networks and (9) expert systems. The methodology for each category is briefly described, the advantages and disadvantages discussed, and the pertinent literature reviewed. Conclusions and comments are made on future research directions.

670 citations

Journal ArticleDOI
TL;DR: A class of switching laws is proposed so that the entire switched system is exponentially stable with a desired stability margin and it is shown quantitatively that, when norms of the perturbations are small, the solutions of the switched systems converge to the origin exponentially under the same switching laws.
Abstract: We study the stability properties of switched systems consisting of both Hurwitz stable and unstable linear time-invariant subsystems using an average dwell time approach. We propose a class of switching laws so that the entire switched system is exponentially stable with a desired stability margin. In the switching laws, the average dwell time is required to be sufficiently large, and the total activation time ratio between Hurwitz stable subsystems and unstable subsystems is required to be no less than a specified constant. We also apply the result to perturbed switched systems where nonlinear vanishing or non-vanishing norm-bounded perturbations exist in the subsystems, and we show quantitatively that, when norms of the perturbations are small, the solutions of the switched systems converge to the origin exponentially under the same switching laws.

593 citations

Journal ArticleDOI
TL;DR: A decentralized multiple-UAV approach to monitoring the perimeter of a fire using a six degree-of-freedom dynamic model for the UAV and a numerical propagationmodel for the forest fire is developed.
Abstract: The objective of this paper is to explore the feasibility of using multiple low-altitude, short endurance (LASE) unmanned air vehicles (UAVs) to cooperatively monitor and track the propagation of large forest fires. A real-time algorithm is described for tracking the perimeter of fires with an on-board infrared sensor. Using this algorithm, we develop a decentralized multiple-UAV approach to monitoring the perimeter of a fire. The UAVs are assumed to have limited communication and sensing range. The effectiveness of the approach is demonstrated in simulation using a six degree-of-freedom dynamic model for the UAV and a numerical propagation model for the forest fire. Salient features of the approach include the ability to monitor a changing fire perimeter, the ability to systematically add and remove UAVs from the team, and the ability to supply time-critical information to fire fighters.

529 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023101
2022207
2021321
2020232
2019212
2018256