Description: 1. A simplified description of how a genetic algorithm works (requiring no knowledge of biology) and how to build your own. 2. A free Excel workbook that allows you to solve problems without doing any coding; or to let you extend the existing code for your own special needs.

Description: An introduction of predictive modeling techniques that are applicable to insurance industry, including generalized linear model (GLM) and classification and regression tree model(CART). Other models such as data clustering, neural network, and support vector machine (SVM), are also briefly discussed.

Description: A summary of the Global Trends 2030 report, the fifth such report produced every four years by the National Intelligence Council. The report is based on the research and analysis of the 17 major intelligence agencies in the US. The summary covers the highlights of the report.

Description: Discussion of several short stories by featured author Steve Mathys. Mathys was the winner of the 10th Speculative Fiction Contest Forecasting and Futurism Section prize.

Description: An introduction to Hidden Markov Models, which are used extensively in speech and facial recognition technology. They are a useful tool in forecasting time series and in developing categorizations of data based on the values of the data themselves.

Description: Discussion of Alternative or Integrative Care - Fundamental themes, market demand, recent activity, developing an alternative care program, pricing benefits Issue No. 34.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.

Description: Agent based modeling is a technique that can be used to predict complex interactions between individuals in an artificial environment. This article provides an introduction to Repast Py.

Description: Deep learning is a method that allows neural networks to be constructed with more than just one or two hidden layers. These layers can then be trained independently and simultaneously of each other. This article provides an introduction to deep belief neural networks.

Description: The winner's curse, applied to Affordable Care Act plan pricing.