9 resultados para fuzzy set

em Aquatic Commons


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Nowadays, risks arising from the rapid development of oil and gas industries are significantly increasing. As a result, one of the main concerns of either industrial or environmental managers is the identification and assessment of such risks in order to develop and maintain appropriate proactive measures. Oil spill from stationary sources in offshore zones is one of the accidents resulting in several adverse impacts on marine ecosystems. Considering a site's current situation and relevant requirements and standards, risk assessment process is not only capable of recognizing the probable causes of accidents but also of estimating the probability of occurrence and the severity of consequences. In this way, results of risk assessment would help managers and decision makers create and employ proper control methods. Most of the represented models for risk assessment of oil spills are achieved on the basis of accurate data bases and analysis of historical data, but unfortunately such data bases are not accessible in most of the zones, especially in developing countries, or else they are newly established and not applicable yet. This issue reveals the necessity of using Expert Systems and Fuzzy Set Theory. By using such systems it will be possible to formulize the specialty and experience of several experts and specialists who have been working in petroliferous areas for several years. On the other hand, in developing countries often the damages to environment and environmental resources are not considered as risk assessment priorities and they are approximately under-estimated. For this reason, the proposed model in this research is specially addressing the environmental risk of oil spills from stationary sources in offshore zones.

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ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

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C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

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Basically this report is an attempt to document trends in oyster recruitment since 1939 and to relate those trends to the actual oyster harvest throughout the Maryland portion of the Chesapeake Bay. It is also hoped that the data as well as the charts compiled in this report will serve as a reference to aid in future studies on Chesapeake Bay oysters. A few if the major biological factors that affect the natural reproduction of the oyster and environmental degradations that may possibly affect oyster reproduction or harvest in the Chesapeake Bay are also briefly discussed. (PDF contains 32 pages)

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Previous authors observed the influence of temperature variations in movement of fishes and noticed better catches in bottom set nets during summer in Tungabhadra reservoir. The present account reports on similar observations in Gobindsagar reservoir.

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This paper describes a set up for a pilot plant with a capacity of 50 kg raw material per batch for the production of fish hydrolysate by enzymatic hydrolysis. Process flow sheet and complete specifications and functions of individual equipment have been described. Multifunctional equipment designed for this pilot plant set up has reduced the number of equipment considerably.

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Results of analysis of part of the data collected during October, 1989 to December, 1990 are given on the biology and catch assessment studies on the Estuarine Set Bagnet (ESBN) from six sampling stations covering the entire coast line of Bangladesh. Length frequency analysis of seven most commonly occurring penaeid shrimp species have been done with complete ELEFAN software package. The result of exploitation patterns indicate that all penaeids except P. stylifera are being over exploited on their way back to the Sea from the nursery ground. This appeared to be the instances of serious growth over fishing. These species are exploited at a size much lower than the length at first maturity, which strongly suggests a complete withdrawal of the bagnet fishery from the coast of Bangladesh.