University of New Brunswick Applies @RISK to Sustainable Seafood Farming
Aquaculture has become a booming industry in many regions of the world. According to the World Bank, nearly two-thirds of the seafood we consume will be farm-raised in 2030. However, commercial aquaculture can have negative environmental impacts, such as high nutrient waste and low oxygen environments. Integrated Multi-Trophic Aquaculture (IMTA) are managed, multi-species aquaculture systems designed to improve environmental management, and increase harvest value through product diversification and recycling of nutrients.
To achieve these benefits, all the interacting components must be understood and carefully optimized. Dr. Gregor Reid, a senior research scientist with the University of New Brunswick, used @RISK to determine the ideal ratios of kelps to uptake soluble metabolites from a salmon IMTA system. A paper detailing this work appeared in the journal Aquaculture in May of 2013.
For his @RISK model, Reid gathered inputs from three diverse sources: the commercial industry, academic literature, and field research. Rather than use single static values for the model inputs, Reid used stochastic distributions for several inputs with ranges of uncertainty, such as digestibility of salmon feed components and nutrient content of IMTA kelps. Known inputs or easily determined values, such as feed composition (listed on all feed bags) could be left as static inputs. Model inputs with sufficient empirical sample data were fit with the @RISK’s distribution fitting functions, testing 15 different theoretical distribution types, and using maximum likelihood estimators to rank the best fits.
After running 10,000 iterations in @RISK, Reid found that “it’s not going to be possible to do full dissolved nutrient recovery with kelps in North America, unless the number of fish being farmed on site is reduced to make room for other species,” He says—but, “one-hundred percent nutrient sequestration doesn’t need to be the only successful endpoint in such systems.”
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Dr. Gregor Reid, Senior Research Scientist,
University of New Brunswick
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Business Analytics: Data Analysis & Decision Making, 5th Edition
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Become a master of data analysis, modeling, and spreadsheet use with Business Analytics: Data Analysis & Decision Making, 5th Edition! This quantitative methods text provides users with the tools to succeed with a teach-by-example approach, student-friendly writing style, and complete Excel 2013 integration. It is also compatible with Excel 2010 and 2007. Problem sets and cases provide realistic examples to show the relevance of the material. The Companion Website includes: the DecisionTools Suite (@RISK, StatTools, PrecisionTree, TopRank, RISKOptimizer, NeuralTools, and Evolver); SolverTable, which allows you to do sensitivity analysis; data and solutions files, PowerPoint slides, and tutorial videos.
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Optimum Utilization of Fly Ash for Stabilization of Sub-Grade Soil using
Jyoti S. Trivedi,
Sandeep Nairb, Chakradhar Iyyunnic
Elsevier, SciVerse Science Direct, Procedia Engineering:
Volume 51, 2013, Pages 250–258
Sub-grade soil stabilization is one of the primary and major processes in the construction of any highway. The aim of this research paper is to formulate a model based on Genetic Algorithm which can be used to predict variation in the values of CBR of the Sub-grade Soil with the addition of a specific percentage of Fly Ash. The input values for this study were those which directly affect the CBR values i.e., directly proportional to CBR. It includes Liquid Limit (LL), Plasticity Index (PI), Optimum Moisture Content (OMC) & Fraction of Fly Ash added (F.A in %). Palisade's Evolver was used for the analysis of stabilization of soil using fly ash.
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