Generalized data stacking programming model with applications

Abstract

Recent researches have shown that, everywhere in various sciences the systems are following stacked-based stored change behavior when subjected to events or varying environments “on and above” their normal situations. This paper presents a generalized data stack programming (GDSP) model which is developed to describe the system changes under varying environment. These changes which are captured with different ways such as sensor reading are stored in matrices. Extraction algorithm and identification technique are proposed to extract the different layers between images and identify the stack class the object follows; respectively. The general multi-stacking network is presented including the interaction between various stack-based layering of some applications. The experiments prove that the concept of stack matrix gives average accuracy of 99.45%.

Keywords

• Consolidity theory
• Extraction algorithm
• Generalized data stacking programming model
• Identification technique
• Multi-stacking networks