2007 Joyce , Monte Carlo simulation as a tool.pdf
| dc.contributor | Joyce | |
| dc.date.accessioned | 2024-03-03T00:03:04Z | |
| dc.date.available | 2024-03-03T00:03:04Z | |
| dc.date.issued | 2007 | |
| dc.description.abstract | New sugar industry projects cost many millions of dollars to complete, so it is not surprising that project financiers want both the technical and financial risks to be properly examined. Conventional deterministic methods for 'what-if' scenarios or sensitivity analyses can be not only tedious to undertake but presenting the results to decision makers can be challenging. Monte Carlo simulation provides a means to not only overcome the limitations of conventional methods but at the same time add levels of sophistication to the analysis that are not otherwise possible. One such advantage is the ability to use a variety of probability distributions to define each input variable. Monte Carlo simulation involves running thousands of scenarios with a dozen or more variables varying simultaneously, to yield the key outputs as probability plots for | |
| dc.identifier | 26 | |
| dc.identifier.uri | https://dochub.sasri.org.za/handle/123456789/22034 | |
| dc.language.iso | En-ZA | |
| dc.publisher | ISSCT | |
| dc.subject | Agriculture :: Sugar Beet Cultivation :: Basic Agronomy :: Planting Methods | |
| dc.title | 2007 Joyce , Monte Carlo simulation as a tool.pdf |
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