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Energy Risk Forum
Calgary, September 25, 2008
Palisade is pleased to announce the first Palisade Energy Risk Analysis forum in Calgary on September 25th, 2008.
The Palisade Energy Risk Analysis Forum is a one-day forum covering risk and decision analysis from all angles specific to the energy sector. From hands-on software training to real-world case studies from industry experts, you will learn new approaches to the problems you face every day. You will also see how new versions of @RISK, PrecisionTree, RISKOptimizer, TopRank, NeuralTools, StatTools, and other Palisade software tools work together to give you the most complete picture possible in your situation. Top-level consultants, industry practitioners, and Palisade experts will present to an audience of professionals in the energy industry.
Whether you are in Oil & Gas, Renewable Energy, Utilities or related Engineering Services, this is an excellent opportunity to network with your peers and fellow @RISK users in your industry.
This webcast is aimed at the practicing product development engineer, quality engineers and technical project managers. Please join us for this journey through these crucial aspects of quality product development and DFSS.
In this presentation the developed approach draws on @RISK software and a traffic assignment model (supported by PTV VISUM software) which makes setting up financing risk analysis in stochastic terms possible, and allows one to benefit from the results coming from @RISK software. In this way, the quality of decision-making is improved by representing traffic demand results in a probabilities distribution histogram, because it allows us to determine the confidence interval for the mean value of traffic demand (or revenue), and identify the most influential input variables for traffic demand through tornado graphics interpretation.
Discounted Cash Flow (DCF)
In this example, the results show that the average DCF is positive (about 40), whereas the probability of a negative DCF is about 15%. The decision as to whether to proceed or not with this project will therefore depend on the risk perspective or tolerance of the decision-maker. .
Impact of Price or Other Variables on Profit:
The release of @RISK 5.0 has spurred tremendous response from our users. Every day customers ask us, “What’s new in @RISK 5.0?” To help answer this question, this series highlights key new features in @RISK 5.0. You can always see a complete list of new features, including short 30-second movies, here:
This is the traditional “bell shaped” curve applicable to distributions of outcomes in many data sets. The Normal distribution is a symmetric continuous distribution which is unbounded on both sides, and described by two parameters (μ and σ i.e. its mean and standard deviation). The use of the Normal distribution can often be justified with reference to a mathematical result called the Central Limit Theorem. This loosely states that if many independent distributions are added together, then the resulting distribution is approximately Normal. The distribution therefore often arises in the real world as the compound effect of more detailed (non-observed) random processes. Such a result applies independently of the shape of the initial distributions being added.
The distribution can be used to represent the uncertainty of a model’s input whenever it is believed that the input is itself the result of many other similar random processes acting together in an additive manner (but where it may be unnecessary, inefficient, or impractical to model theses detailed driving factors individually). Examples could include the total number of goals scored in the a soccer season, the amount of oil in the world, assuming that there are many reservoirs of approximately equal size, but each with an uncertain amount of oil. Where the mean is much larger than the standard deviation (e.g. 4 times or more) then a negative sampled value of the distribution would occur only rarely (so that the number of goals would not be sampled negatively in most practical cases). More generally, the output of many models is approximately normally distributed, because many models have an output which results from adding many other uncertain processes. An example might be the distribution of discounted cash flow in a long-term time series models, which consists of summing the discounted cash flows from the individual years.
RiskNormal(mean,standard deviation) specifies a normal distribution with the entered mean and standard deviation.
RiskNormal(10,2) specifies a normal distribution with a mean of 10 and a standard deviation of 2.
RiskNormal(SQRT(C101),B10) specifies a normal distribution with a mean equaling the square root of the value in cell C101 and a standard deviation taken from cell B10.
A new set of online decision tools developed at Montana State University help farmers select fertilizer, herbicides, and plant varieties.
Neural networks are helping astronomers overcome an age-old enemy of their profession: information overload.
A new tool to help financial executives plan and control energy costs uses @RISK 5.0 to run the Monte Carlo simulation component of its analysis.
Danish researchers have used neural networks to decode the genetic material of the human immune system. Their models predict the immune system’s access codes and simulate how the body protects itself from disease.
Australian researchers are developing a bridge management system that incorporates a neural network to predict the safety of 10,000 bridges across Queensland.
GIS and data mining are naturally synergistic technologies that can be harnessed together to produce powerful market insight from a sea of disparate data.
The space mission known will run Monte Carlo simulation with satellite observations of the ocean surface to help offshore oil and gas drilling operations avoid dangerous underwater eddies.
Of the many, many inmates on death row, only a few will eventually be executed. A new study uses neural networks to find out what characterizes these inmates.
Each of the robots punk musician Fiddian Warman has planted in his audience is controlled by a neural network, which has "educated" the robots in the finer points of punk.
One youth worker with a Yale M.B.A. is sharing the decision analysis techniques she learned in business school with kids in trouble.
A new wireless neural network technology will link streetlights with parking meters to allow consumers to see which parking spaces are available.
The Palisade User Forums are online discussion boards where users are invited to post questions and share ideas on their use of @RISK and other Palisade software. It’s also a great place to check for announcements regarding updates of Palisade software. Forums are organized by products.
Recent topics include:
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