Now Data are clearly prevailing in all domains like a new black gold for companies and the rules in business decision-making are called into question. In this context, we think that Data Analytics combined with collaborative decision processes promotes a rational decision-making. However best practices show that more and more executives and managers, the famous HiPPO (Highest Paid Person’s Opin...

Evidence-based medicine intends to optimize clinical decision making by using evidence. Semantic query answering could help to find the most relevant evidence. However, at point of care, it still lacks time for clinicians to do literature study. In this poster, we propose to build an evidence graph for clinical decision support, in which an evidence ontology is defined with extension of SWRL ru...

In semiconductor fabrication, dynamic interactions among chamber deterioration, operation characteristics, and wafer yield necessitate an intelligent decision making policy for maintenance. However, only simple heuristic rules for maintenance scheduling are currently employed in semiconductor fabs. Therefore, there is a clear need for a more formal framework for maintenance decision making. The...

An approach to decision making that integrates multi-attribute decision techniques with expert systems is described. The approach is based on the explicit articulation of qualitative decision knowledge which is represented by a tree of attributes and decision rules. The decision making process is supported by a specialized expert system shell for interactive construction of the knowledge base, ...

Stochastic programming provides a versatile framework for decision-making under uncertainty, but the resulting optimization problems can be computationally demanding. It has recently been shown that primal and dual linear decision rule approximations can yield tractable upper and lower bounds on the optimal value of a stochastic program. Unfortunately, linear decision rules often provide crude ...

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike laten...

There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...