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What is Fuzzy Variable

Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications
A variable that depicts some imprecise, linguistic, or vague characteristics.
Published in Chapter:
Fuzzy System Dynamics of Manpower Systems
Michael Mutingi (University of Johannesburg, South Africa & University of Botswana, Botswana) and Charles Mbohwa (University of Johannesburg, Johannesburg, South Africa)
DOI: 10.4018/978-1-4666-4450-2.ch030
Abstract
Manpower recruitment and training in uncertain and turbulent environments is a challenge to decision makers in large organizations. In the absence of numerical precision on market growth and the ensuing manpower demand, designing manpower planning policies is vital. Often times, companies incur losses due to overstaffing and/or understaffing. For instance, organizations lose business when critical human resources leave. As a result, it is essential to develop robust effective dynamic recruitment and training policies, especially in a fuzzy and dynamic environment. In this chapter, a fuzzy systems dynamics modeling approach is developed to simulate and evaluate alternative dynamic policies relating skills recruitment, skills training, and available skills from a systems thinking perspective. Fuzzy system dynamics is implemented based on fuzzy logic and system dynamics concepts in order to arrive at robust strategies for manpower decision makers. It is anticipated that fuzzy system dynamics can help organizations to design effective manpower recruitment strategies in a dynamic and uncertain environment.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Fuzzy Expert System in Agriculture Domain
A quantity that can take on linguistic values. For example, the fuzzy variable “disease” might have values such as “low,” “medium,” or “high.”
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Enhanced Fuzzy Assessment Methodology to Find Overlapping in Membership Function Using K Ratio to Find the Yield of Rice
In fuzzy logic, a quantity that can take on linguistic rather than precise numerical values. For example, a fuzzy variable, yield might have values such as “high,” “medium,” and “low.”
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Risk Factor in Agricultural Sector: Prioritizing Indian Agricultural Risk Factor by MAUT Method
A quantity that can take on linguistic values. For example, the fuzzy variable ‘disease’ might have values such as ‘low’, ’medium’, or ‘high’.
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Agricultural Health and Safety Measures by Fuzzy ahp and Prediction by Fuzzy Expert System: Agricultural Risk Factor
A quantity that can take on linguistic values. For example, the fuzzy variable “disease” might have values such as “low” or “high.”
Full Text Chapter Download: US $37.50 Add to Cart
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