Fuzzy cognitive maps for policy analysis

Perusich, Karl

doi:10.1109/istas.1996.541174

Cited by 29 publications

(14 citation statements)

References 5 publications

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“…After the updating procedure in (12), the following cost function is considered for obtaining the optimum weight matrix W [8]:…”

Section: Hebbian Learning Based Algorithm;mentioning

confidence: 99%

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Heuristic Search Applied to Fuzzy Cognitive Maps Learning

Angélico¹,

Mendonça²,

Arruda³

et al. 2013

Search Algorithms for Engineering Optimization

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“…After the updating procedure in (12), the following cost function is considered for obtaining the optimum weight matrix W [8]:…”

Section: Hebbian Learning Based Algorithm;mentioning

confidence: 99%

“…FCM has been considered with great research interest in many scientific fields, such as political decision [5], medical decision [6,7], industrial process control [8,9], artificial life [10], social systems [11], corporative decision, policy analysis [12], among others.…”

Section: Introductionmentioning

confidence: 99%

Heuristic Search Applied to Fuzzy Cognitive Maps Learning

Angélico¹,

Mendonça²,

Arruda³

et al. 2013

Search Algorithms for Engineering Optimization

View full text Add to dashboard Cite

“…References [2] and [54] have used FCM for representing tacit knowledge in political and social analysis. FCMs have been successfully applied to various fields such as decision making in complex war games [29], strategic planning [12], [57], strategic information systems planning [25], information retrieval [21], and distributed decision modeling [68].…”

Section: Fuzzy Cognitive Maps (Fcms) 1) Definitions and Algorithmsmentioning

confidence: 99%

Fuzzy Cognitive Maps in Business Analysis and Performance-Driven Change

Xirogiannis

Glykas

2004

IEEE Trans. Eng. Manage.

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Abstract-Business process reengineering (BPR) has made a significant impact on managers and academics. Despite the rhetoric surrounding BPR, articulated mechanisms, which support reasoning on the effect of the redesign activities to the performance of the business model, are still emerging. This paper describes an attempt to build and operate such a reasoning mechanism as a novel supplement to performance-driven change (PDC) exercises. This new approach proposes the utilization of the fuzzy causal characteristics of fuzzy cognitive maps (FCMs) as the underlying methodology in order to generate a hierarchical and dynamic network of interconnected performance indicators. By using FCMs, the proposed mechanism aims at simulating the operational efficiency of complex process models with imprecise relationships to quantify the impact of performance-driven reengineering activities. This research also establishes generic maps that supplement the strategic planning and business analysis phases of typical redesign projects in order to implement the integration of hierarchical FCMs into PDC activities. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.

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“…Applications of FCM are found in many fields of science, such as artificial life [11], social systems [12], modeling and decision make in corporative environments, in rapid access highways [13], in medical field [8], among others. In this paper, two FCM models for process control problems, described in [9] and [10], are considered.…”

mentioning

confidence: 99%

A comparative analysis of three metaheuristic methods applied to fuzzy cognitive maps learning

et al. 2013

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ABSTRACT. This work analyses the performance of three different population-based metaheuristic approaches applied to Fuzzy cognitive maps (FCM) learning in qualitative control of processes. Fuzzy cognitive maps permit to include the previous specialist knowledge in the control rule. Particularly, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and an Ant Colony Optimization (ACO) are considered for obtaining appropriate weight matrices for learning the FCM. A statistical convergence analysis within 10000 simulations of each algorithm is presented. In order to validate the proposed approach, two industrial control process problems previously described in the literature are considered in this work.

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Fuzzy cognitive maps for policy analysis

Cited by 29 publications

References 5 publications

Heuristic Search Applied to Fuzzy Cognitive Maps Learning

Heuristic Search Applied to Fuzzy Cognitive Maps Learning

Fuzzy Cognitive Maps in Business Analysis and Performance-Driven Change

A comparative analysis of three metaheuristic methods applied to fuzzy cognitive maps learning

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