Software package and API in MATLAB for working with fuzzy algebras

Zahariev, Z.; Venkov, George; Kovacheva, Ralitza; Pasheva, Vesela

doi:10.1063/1.3271635

Cited by 8 publications

(10 citation statements)

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“…At this moment this software supports one application -ftizzy optimization problems as described in [4], [6], [6], and [7]. Because of this reason it is designed to be as easy to be extended as possible.…”

Section: Discussionmentioning

confidence: 99%

Software for Solving Fuzzy Linear Systems

Atanasov¹,

Peeva²,

Venkov³

et al. 2009

AIP Conference Proceedings

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Articles you may be interested inPower management strategy based on adaptive neuro-fuzzy inference system for fuel cellbattery hybrid vehicle Abstract. The paper presents method, algorithm and software in Java for solving iiizzy linear systems of equations or flizzy linear systems of inequalities. We implement software for calculating all minimum and maximum solutions of flizzy linear systems when the composition is max-min, min-max and max-product.

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Section: Discussionmentioning

confidence: 99%

Software for Solving Fuzzy Linear Systems

Atanasov¹,

Peeva²,

Venkov³

et al. 2009

AIP Conference Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

“…Direct problem is solvable in polynomial time. Software for direct problem resolution is given in [20][21][22]. It provides all the operations and algorithms described in Table 1 in MATLAB environment.…”

Section: Direct and Inverse Problemsmentioning

confidence: 99%

“…Efficient algorithms for finding the complete solution set of ( 5) are given in [20][21][22]. A software implementations are given in [3,21,22]. We will use the software implementation from [22].…”

Section: Solutions Of the Inverse Problem For (5)mentioning

confidence: 99%

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Optimising Sensor Controlled Systems With Minimal Intervention: A Fuzzy Relational Calculus Approach

Zahariev

2024

Preprint

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This article describes an approach for optimising sensor-controlled systems through minimal intervention, utilising Fuzzy Linear Systems of Equations (FLSE). Staring with a generalised model of the system behaviour, incorporating an array of control units, environmental sensors, and an expert knowledge base. The described problems of detecting the level of intervention needed to change the system state to another is handled with the help of developed methods for solving the inverse problem for FLSE. By achieving minimal intervention, we ensure that system adjustments effective, economically optimal and non-intrusive. A MATLAB-based implementation is presented.

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“…Notice that, although Matlab is commercially distributed, the toolboxes enumerated below are freely released by their authors. Some examples of Matlab toolboxes are: IT2FLS [58], which extends the Matlab fuzzy logic toolbox in order to support the design of interval type-2 fuzzy systems; XTRIG [59], which performs fuzzy qualitative trigonometry in terms of 4-tuple fuzzy numbers; Fuzzy Calculus CORE [60], which supports various fuzzy algebras dealing with fuzzy linear systems of equations and inequalities; etc. An example of R toolbox is the R fuzzy-toolbox [61], which is expected to be somewhat equivalent to the well-known fuzzy toolbox provided by Matlab [11].…”

Section: General Purpose Fuzzy Systems Toolboxesmentioning

confidence: 99%

A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

Alcalá‐Fdez

Alonso

2016

IEEE Trans. Fuzzy Syst.

106

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Fuzzy systems have been used widely thanks to their ability to successfully solve a wide range of problems in different application fields. However, their replication and application requires a high level of knowledge and experience. Furthermore, few researchers publish the software and/or source code associated with their proposals, which is a major obstacle to scientific progress in other disciplines and in industry. In recent years, most fuzzy system software has been developed in order to facilitate the use of fuzzy systems. Some software is commercially distributed but most software is available as free and open source software, reducing such obstacles and providing many advantages: quicker detection of errors, innovative applications, faster adoption of fuzzy systems, etc. In this paper, we present an overview of freely available and open source fuzzy systems software in order to provide a well-established framework that helps researchers to find existing proposals easily and to develop well founded future work. To accomplish this, we propose a twolevel taxonomy and we describe the main contributions related to each field. Moreover, we provide a snapshot of the status of the publications in this field according to the ISI Web of Knowledge. Finally, some considerations regarding recent trends and potential research directions are presented.

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Software package and API in MATLAB for working with fuzzy algebras

Cited by 8 publications

References 0 publications

Software for Solving Fuzzy Linear Systems

Software for Solving Fuzzy Linear Systems

Optimising Sensor Controlled Systems With Minimal Intervention: A Fuzzy Relational Calculus Approach

A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends, and Prospects

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