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Predictive Maintenance Using Modified FMECA Method

Srivastava, Nishit - 2016

This paper proposes a predictive maintenance policy using modified failure mode effect and criticality analysis (Mod-FMECA) technique. FMECA is used to identify failure modes, reasons, effects and criticality of the system (machine/plant) but in Mod-FMECA in addition to the analysis carried for...

Persistent link: https://www.econbiz.de/10012987127

Predictive Maintenance Using FMECA Method and NHPP Models

Srivastava, Nishit; Mondal, Sandeep - 2016

Most of predictive maintenance technologies are inaccessible to small scale and medium scale industries due to their demanding cost. This paper proposes a predictive maintenance policy using failure mode effect and criticality analysis (FMECA) and non-homogeneous Poisson process (NHPP) models...

Persistent link: https://www.econbiz.de/10014034899

Predicting Compliance : Leveraging Chat Data for Supervised Classification in Experimental Research

Hausladen, Carina Ines; Fochmann, Martin; Mohr, Peter - 2023

Many experimental research designs offer participants the opportunity to chat with each other. While experimental research has traditionally treated text as process data, this paper proposes a novel approach to interpret and use chat data in a structured supervised classification task....

Persistent link: https://www.econbiz.de/10014255468

Evaluating Performance of Regression Machine Learning Models Using Multiple Error Metrics in Azure Machine Learning Studio

Botchkarev, Alexei - 2018

Data driven companies effectively use regression machine learning methods for making predictions in many sectors. Cloud … limitations, e.g. small number of performance metrics and lack of functionality to evaluate custom built regression models with R … evaluation of the regression models. EEM offers 4 times more metrics than built-in Azure Evaluate Model module. EEM metrics …

Persistent link: https://www.econbiz.de/10012919484

Predicting welfare effects of food price shocks : a comparative analysis

Rischke, Ramona - 2015

Following the 2007/09 and subsequent world food price shocks, a growing number of simulation studies predicted their implications on food security. Studies that only require pre-price-hike data and the specification of relevant price or income changes have been advocated as a potential tool to...

Persistent link: https://www.econbiz.de/10010530130

Predicting financial stress events : a signal extraction approach

Christensen, Ian; Li, Fuchun - 2014

The objective of this paper is to propose an early warning system that can predict the likelihood of the occurrence of financial stress events within a given period of time. To achieve this goal, the signal extraction approach proposed by Kaminsky, Lizondo and Reinhart (1998) is used to monitor...

Persistent link: https://www.econbiz.de/10010400740

Linking series generated at different frequencies and its applications

Hyung, Namwon - 1998

This paper systematically studies the use of mixed-frequency data sets and suggests that the use of high frequency data in forecasting economic aggregates can improve forecast accuracy. The best way of using this information is to build a single model, for example, an ARMA model with missing...

Persistent link: https://www.econbiz.de/10010503744

How to Predict the Frequency of Voting Events in Actual Elections

Plassmann, Florenz - 2012

Two commonly-used criteria for evaluating voting rules are how infrequently the rules provide opportunities for strategic voting and how infrequently they encounter voting paradoxes. The lack of ranking data from enough actual elections to determine these frequencies with reasonable accuracy...

Persistent link: https://www.econbiz.de/10013114263

Forecasting and Trading High Frequency Volatility on Large Indices

Liu, Fei - 2018

The present paper analyzes the forecastability and tradability of volatility on the large S&P500 index and the liquid SPY ETF, VIX index and VXX ETN. Even though there is already a huge array of literature on forecasting high frequency volatility, most publications only evaluate the forecast in...

Persistent link: https://www.econbiz.de/10012935482

Improving Forecasts Using Equally Weighted Predictors

Graefe, Andreas - 2017

reduced the forecast error of the original regression models on average by four percent. An equal-weights model that includes … all variables provided well-calibrated forecasts that reduced the error of the most accurate regression model by 29 …

Persistent link: https://www.econbiz.de/10012974080

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