Comparação entre redes bayesianas do tipo naive bayes baseadas na distribuição exponencial

This paper compares and evaluates the precision of four evaluators of Naive Bayes based on the Exponentional Distribution. The acquired results were analysed according to the percentage of correct classification, the coefficient Kappa, its variance and the time of CPU consumed for each method. To analyse the performance of the methods, two groups of samples called training and testing samples, each having data from 1 to 4 dimensions with four different classes of performance. For the training samples with 10.000 observations were created for each and for the test samples were generated 16 samples with 30.000 observations. As result, the Method of Assessment and Training in the Fuzzy Exponentional Naive Bayes Network was significally better than the others. In relation to the time of CPU consumed, MATRENB managed to evaluate data that followed the Exponential Distribution, with four dimensions, therefore is a low computational cost application. It is worth to mention that from three or more dimensions most of the evaluators managed to acquire a percentual hits, with a moderate degree of substancial agreement, according to the Kappa coefficient.NenhumaEste trabalho compara e avalia a precisão de quatro avaliadores do tipo Naive Bayes baseados na distribuição Exponencial. Os resultados obtidos foram analisados de acordo com o Acerto Percentual, o Coeficiente Kappa, sua variância e o Tempo Computacional de cada método. Para analisar a performance dos métodos foram geradas dois conjuntos de amostras denominadas Amostras para Treinamento e Teste, que possuem dados de 1 a 4 dimensões com quatro classes de desempenho distintas. Para a amostra de treinamento foi gerada 16 amostras com 10000 observações cada e para amostra de teste foram geradas 16 amostras cada uma com 30000 observações. Como resultados obteve-se que o Método de Avaliação de treinamento na Rede Fuzzy Exponencial Naive Bayes (MATRENB) foi significativamente melhor que os demais. Em relação ao tempo computacional o MATRENB conseguiu avaliar dados que seguem uma Distribuição Exponencial, com quatro dimensões, com um baixo custo computacional. Vale ressaltar, que a partir de três ou mais dimensões a maioria dos avaliadores conseguiram obter um percentual de acertos, com um grau de concordância moderado, de acordo com o coeficiente Kappa

Risk Management for the Future

A large part of academic literature, business literature as well as practices in real life are resting on the assumption that uncertainty and risk does not exist. We all know that this is not true, yet, a whole variety of methods, tools and practices are not attuned to the fact that the future is uncertain and that risks are all around us. However, despite risk management entering the agenda some decades ago, it has introduced risks on its own as illustrated by the financial crisis. Here is a book that goes beyond risk management as it is today and tries to discuss what needs to be improved further. The book also offers some cases

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The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development

The protection and maintenance of environmental resources for future generations require responsible interaction between humans and the environment in order to avoid wasting natural resources. According to an ancient Native American proverb, “We do not inherit the Earth from our ancestors; we borrow it from our children.” This indigenous wisdom has the potential to play a significant role in defining environmental sustainability. Recent technological advances could sustain humankind and allow for comfortable living. However, not all of these advancements have the potential to protect the environment for future generations. Developing societies and maintaining the sustainability of the ecosystem require appropriate wisdom, technology, and management collaboration. This book is a collection of 19 important articles (15 research articles, 3 review papers, and 1 editorial) that were published in the Special Issue of the journal Sustainability entitled “Appropriate Wisdom, Technology, and Management toward Environmental Sustainability for Development” during 2021-2022.addresses the policymakers and decision-makers who are willing to develop societies that practice environmental sustainability, by collecting the most recent contributions on the appropriate wisdom, technology, and management regarding the different aspects of a community that can retain environmental sustainability

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