This paper aims to establish a predictive model for battery lifetime using data analysis. The procedure of establishment is illustrated in detail, including the pre-processing, modeling, and prediction. characteristics lithium-ion batteries are introduced. In this study, analysis performed with MATLAB, open-source provided by NASA. addressed models include decision tree, nonlinear autoregressio...

NAND flash memory – ubiquitous in today’s world of smart phones, SSDs (solid state drives), and cloud storage has a number well-known reliability problems. data contains bit errors, which require the use error correcting codes (ECCs). The raw rate (RBER) increases with program-erase (P-E) cycling, P-E cycles device can withstand before RBER exceeds ECC capability is called its endurance. operat...

Financial distress prediction (FDP) has always been an important issue in the business and financial management. This research proposed a novel multiple classifier ensemble model based on firm life cycle and Choquet integral for FDP, named MCELCCh-FDP, as a new approach to tackle with financial distress. Empirical study based on Chinese listed companies’ real data is conducted, and the results ...

We consider the prediction algorithm and performance evaluation for prognostics and health management (PHM) problems, especially the prediction of remaining useful life (RUL) for the milling machine cutter and lithium‐ion battery. We modeled battery as a voltage source and internal resisters. By analyzing voltage change trend during discharge, we made the prediction of battery remain discharge ...

Accurate prediction of the remaining useful life of a faulty component is important to the health management of the system. It gives operators information about when the component should be replaced. This paper studied the remaining useful life prediction of the lithium-ion batteries. Some work has been done to solve this problem, but it still remains challengeable. Particle filter (PF) is a re...