We propose a continuous maximum entropy method to investigate the robust optimal portfolio selection problem for the market with transaction costs and dividends. This robust model aims to maximize the worst-case portfolio return in the case that all of asset returns lie within some prescribed intervals. A numerical optimal solution to the problem is obtained by using a continuous maximum entrop...

Risk is anything that threatens the successful achievement of a project’s goals. The fundamental principle of risk-based testing is to do more thorough testing to those parts of the software system that present the highest risk. In this fast abstract, we introduce risk-based testing and discuss applying risk analysis to select test cases for regression testing which is essential to ensure softw...

A recognition network is a multilayer per­ ception (MLP) trained to predict posterior marginals given observed evidence in a par­ ticular Bayesian network. The input to the MLP is a vector of the states of the eviden­ tial nodes. The activity of an output unit is interpreted as a prediction of the posterior marginal of the corresponding variable. The MLP is trained using samples generated from ...

Feature Weighting is one of the most difficult tasks when developing Case Based Reasoning applications. This complexity grows when dealing with ill-defined wide domains with a sparse case base. Moreover, most widely-used feature selection and feature weighting methods assume that features are either relevant in the whole instance space or irrelevant through-out. However, it is often the case th...

reducing test suite size without compromising the suite’s effectiveness in performing regression testing. This article presents a hybrid technique using the variable-based method that combines both selection and prioritization. It considers source code changes and coverage information with respect to each test case. Variables are the vital source of changes in the program, and this method captu...

Two methods have been proposed for manipulating uncertainty reflecting designer choice: utility theory and the method of imprecision. Both methods represent this uncertainty across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. The two methods can differ, however, in the combination metrics used to combine the ranks of the incommensurate design ...

An appropriate project delivery system (PDS) is crucial to the success of a construction projects. Case-based Reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly sam...