Essay on Mamdani-Type and Sugeno-Type Fuzzy Inference Systems for Air Conditioning

2021-05-27 06:33:46
4 pages
936 words
University/College: 
Vanderbilt University
Type of paper: 
Creative writing
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Every computer system relies on the ability of its components to keep actively engaged in the multi-functional communication within the computer, to ensure that the end user's needs get met. To that effect, every computer system must have its components working under controlled temperatures so as to avoid malfunctioning of the machine and even loss of valuable data. The Sugeno-type and Mamdani-type Fuzzy inference system based controllers for the fan of the computer ensure that the computer electronic components do not overheat, and they do so by cooling the said components. Mamdani-type differs from Sugeno-type fuzzy inference system regarding performance in several ways.

Regarding the fulfillment of the operation, (Adewuyi, Pg 35) argues that Sugeno-type fuzzy inference based controller works smoother compared to the Mamdani-type whose effectiveness does not provide as much cooling effect. Reason being, the Sugeno-type system has more compact representation efficiency and has the better computational capability. Also, the Mamdani-type system works to an incomplete capacity compared to the Sugeno-type fuzzy inference system based controller which exhausts a full cycle of working. There is the most efficient response of the Sugeno-type fuzzy inference system compared to the Mamdani-type, to the values of input and also according to the working variations of input quantities (Kaur, Kaur, Pg. 2).

The crisp output between the Sugeno-type and Mamdani-type fuzzy inference systems stands as the primary distinguishing factor. That is, the Sugeno-type FIS utilizes the weighted average while Mamdani-type utilizes the defuzzification style in crisp output computation. The degree of interpretation and the Mamdani-type expressive power diminishes in the Sugeno-type FIS whose processing time is better. That is, the performance and adaptability of the computer system is made more flexible by the Sugeno-type fuzzy inference system.

Approach to Risk Mitigation

The primary purpose of identifying risk and analyzing the same risk gets done in preparation for mitigation of risk. Mitigation involves minimization of the possibility of occurrence of risk and also the reduction of the aftermath of the risk in question if, that risk happens. Several ways apply in the successful mitigation of risk.

Risk acceptance gets used after running the analysis of cost-benefit which makes the determination of whether the mitigating risk is more expensive, compared to the cost of bearing the same risk. In that case, the most appropriate response becomes accepting the risk while also having continued risk monitoring. Avoidance of risk gets applied as a mitigation approach when the activities involved have a significant possibility of a significant adverse financial blow or any other kind of loss. In such an instance, avoiding the whole activity which has the potential of great adversity becomes the only alternative.

Risk limitation gets applied as a strategy that minimizes risk to an acceptable level that makes sure that a firm gets part cover from the occurrence of the risk. For instance, a company will apply risk limitation against the occurrence of floods by accepting the fact that a tsunami may happen and also avoid the possibility of loss of its assets by having an insurance cover against floods. Risk transference also called risk contracting refers to the allocation of risks to entities that are best placed to handle and manage the risks. The challenge occurs however when there is the absence of quantitative measurement of the risk which could cause lack of accountable responsibility in looking for mutual threats that have optimal allocation. Quantifying risk is, therefore, necessary.

Planning for risk mitigation helps in settling on the best approach to curbing the potential in question, based on its efficiency and effectiveness (Sjoberg, Pg. 130). There are several applicable methods of reducing risk based on the perspective of systems engineering in the order of intensity of risk. They include In-depth reviews of the process of engineering both technically and management wise; peculiar supervision of the allocated engineering parameters and different testing and analysis of important objects of design. Also, quick prototype formation and feedback from tests; making consideration to make a relief of relevant requirements of design and lastly, starting backup parallel developments.

The management and mitigation of risk do not happen at free cost regardless of whether one is handling low-probability or high impact hazards. (National Research Council of the National Academies, Pg. 41) Views that, It is because it becomes necessary to identify unusual activities involved in mitigation of risk. Notably, a plan of risk management defines the framework of managing the risk of a project while a program of risk reduction describes the wholesome risk and the plan of action response. For instance, implementing the reduction of parallel developments could assist the government in calculating the possibility of the cost involved being twice as much. On the other hand, putting into consideration fast prototyping or making alterations to the operational needs could spark the idea of making a projection of the likely time and cost to get incurred during risk mitigation.

Final Thoughts

However, even though risks may get accepted, avoided, transferred or limited, the idea of risk assumption could necessitate where the danger of implementing a project is a smaller compared to the risk of failing to proceed forward.

 

Works Cited

Adewuyi, Philip. Performance Evaluation of Mamdani and Sugeno-type Fuzzy Inference System Based Controllers of Computer Fan. Information Technology and Computer Sciences. University of Lagos, Nigeria. 2012. Print

Kaur, Arshdeep, and Kaur, Amrit. Comparison of Mamdani-type and Sugeno-Type fuzzy inference systems for air conditioning. International Journal of Soft Computing and Engineering (IJSCE). Vol.2, Issue-2. 2012. Print

National Research Council of the National Academies. The Owners Role in Project Risk Management. Available in: (https://www.nap.edu/read/11183/chapter/7). 2005 .Pg. 41. Print

Sjoberg, Lennart. Consequences of perceived risk: Demand for mitigation. Journal of risk research 2.2 (1999. Print

 

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