In this work we introduce a framework, based on three-way decision (TWD) and the
trisecting-acting-outcome model, to handle uncertainty in Machine Learning (ML). We …

Causality has been a subject of study for a long time. Often causality is confused with
correlation. Human intuition has evolved such that it has learned to identify causality through …

This paper develops and presents a novel technique for missing data estimation using a
combination of dynamic programming, neural networks and genetic algorithms (GA) on …

In today's society, there are plenty of services available, and customers are facing bigger
challenge in choosing them than ever before. Therefore, it is important to build a reliable …

With the approaching of cloud and big data computing era, renewable energy such as solar
energy is increasingly integrated into data center power provisioning systems. Nevertheless …

This chapter describes in detail the problem of missing data. It also describes the different
missing data patterns and mechanisms. This is followed by a discussion of the classical …

Finance has a great impact on real economy's development. From a historical perspective,
financial innovation is often coupled with technological advancement. Among various …

In this paper the theory of flexibly-bounded rationality which is an extension to the theory of
bounded rationality is revisited. Rational decision making involves using information which …

This paper presents a method of imputing missing data that combines principal component
analysis and neuro-fuzzy (PCA-NF) modeling in conjunction with genetic algorithms (GA) …

Missing data problem degrades the statistical power of any analysis made in clinical studies.
To infer valid results from such studies, suitable method is required to replace the missing …