In most situations, we can only collect small samples for modeling specific economic forecasting problems. Thus, the availability of accurate predictive model for small samples is vital for solving these problems. This research makes an early investigation on the small sample-oriented case-based...

Previous studies on financial distress prediction (FDP) almost construct FDP models based on a balanced data set, or only use traditional classification methods for FDP modelling based on an imbalanced data set, which often results in an overestimation of an FDP model’s recognition ability for...

Electre is an important outranking method developed in the area of decision-aiding. Data mining is a vital developing technique that receives contributions from lots of disciplines such as databases, machine learning, information retrieval, statistics, and so on. Techniques in outranking...

Case-based reasoning (CBR) is a very effective and easily understandable method for solving real-world problems. Business failure prediction (BFP) is a forecasting tool that helps people make more precise decisions. CBR-based BFP is a hot topic in today's global financial crisis. Case...

We study a game model of multi-leader and one-follower in supply chain optimization where n suppliers compete to provide a single product for a manufacturer. We regard the selling price of each supplier as a pre-determined parameter and consider the case that suppliers compete on the basis of...

A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the US industrial and financial firms spanning the period 1991–2011 on a monthly basis. Several commonly used...

In this paper we consider cardinality-constrained convex programs that minimize a convex function subject to a cardinality constraint and other linear constraints. This class of problems has found many applications, including portfolio selection, subset selection and compressed sensing. We...