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Demand Trend Mining for Predictive Life Cycle Design
16 references·6 citing·41 second hop
Demand Trend Mining for Predictive Life Cycle Design (2014)Demand Trend Mining for Predictive Life C…Challenges and opportunities with big data (2012)Challenges and opportunities …Forecasting with Exponential Smoothing : The State Space Approach (2008)Forecasting with Exponential …Automatic Time Series Forecasting: The forecast Package for R (2008)Automatic Time Series Forecas…25 years of time series forecasting (2006)25 years of time series forec…Enhancing Discrete Choice Demand Modeling for Decision-Based Design (2004)Enhancing Discrete Choice Dem…An Approach to Decision-Based Design With Discrete Choice Analysis for Demand Modeling (2003)An Approach to Decision-Based…Incorporating component reuse, remanufacture, and recycle into product portfolio design (2002)Incorporating component reuse…A state space framework for automatic forecasting using exponential smoothing methods (2002)A state space framework for a…Discrete Choice Methods with Simulation (2001)Discrete Choice Methods with …Using Conjoint Analysis to Help Design Product Platforms (1999)Using Conjoint Analysis to He…Implications of Modularity on Product Design for the Life Cycle (1998)Implications of Modularity on…Remanufacturing : the experience of the United States and implications for developing countries (1985)Remanufacturing : the experie…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Box-Jenkins Methods: An Alternative to Econometric Models (1972)Box-Jenkins Methods: An Alter…D3 framework: An evidence-based data-driven design framework for new product service development (2024)D3 framework: An evidence-bas…Big data analytics in flexible supply chain networks (2023)Big data analytics in flexibl…Data Mining in Product Portfolio and Variety Management – Literature Review on Use Cases and Research Potentials (2021)Data Mining in Product Portfo…Smart recovery decision-making for end-of-life products in the context of ubiquitous information and computational intelligence (2020)Smart recovery decision-makin…A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making (2020)A framework for data-driven d…Optimal Line Design of New and Remanufactured Products: A Model for Maximum Profit and Market Share with Environmental Consideration (2018)Optimal Line Design of New an…Fundamentals of Product Modularity (1994)Product modularization for life cycle engineering (1999)Product modularity: measures and design methods (2003)A Network Approach to Define Modularity of Components in Complex Products (2007)PRODUCT DESIGN AND DEVELOPMENT (2018)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Another look at measures of forecast accuracy (2006)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)On the use of cross-validation for time series predictor evaluation (2012)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Time series forecasting of petroleum production using deep LSTM recurrent networks (2018)Conditional logit analysis of qualitative choice behavior (1972)Specification Tests in Econometrics (1978)Automobile Prices in Market Equilibrium (1995)A latent class model for discrete choice analysis: contrasts with mixed logit (2003)The Mixed Logit model: The state of practice (2003)Conducting Discrete Choice Experiments to Inform Healthcare Decision Making (2008)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Forecasting methods and applications (1993)The M3-Competition: results, conclusions and implications (2000)Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)A new metric of absolute percentage error for intermittent demand forecasts (2016)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Big data: The next frontier for innovation, competition, and productivity (2011)Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (2014)Big Data and cloud computing: innovation opportunities and challenges (2016)Machine Learning With Big Data: Challenges and Approaches (2017)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Generalized autoregressive conditional heteroskedasticity (1986)Principles of forecasting : a handbook for researchers and practitioners (2001)The politics of attention: how government prioritizes problems (2006)Exponential smoothing: The state of the art (1985)Using daily stock returns (1985)A note on the validity of cross-validation for evaluating autoregressive time series prediction (2017)A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting (2019)An optimized model using LSTM network for demand forecasting (2020)
this work references cited by second hop

References

  • 1977Time Series Analysis: Forecasting and Control19,200 cited
  • 2001Discrete Choice Methods with Simulation7,780 cited
  • 1977Time Series Analysis: Forecasting and Control6,446 cited
  • 1978Time Series Analysis: Forecasting and Control.5,299 cited
  • 2008Automatic Time Series Forecasting: The forecast Package for R3,538 cited
  • 200625 years of time series forecasting1,589 cited
  • 2002A state space framework for automatic forecasting using exponential smoothing methods1,074 cited
  • 2012Challenges and opportunities with big data1,068 cited
  • 2008Forecasting with Exponential Smoothing : The State Space Approach818 cited
  • 1998Implications of Modularity on Product Design for the Life Cycle280 cited
  • 2003An Approach to Decision-Based Design With Discrete Choice Analysis for Demand Modeling251 cited
  • 1999Using Conjoint Analysis to Help Design Product Platforms182 cited
  • 1972Box-Jenkins Methods: An Alternative to Econometric Models174 cited
  • 2002Incorporating component reuse, remanufacture, and recycle into product portfolio design166 cited
  • 2004Enhancing Discrete Choice Demand Modeling for Decision-Based Design156 cited

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  • 1985Remanufacturing : the experience of the United States and implications for developing countries153 cited
  • Cited by

    • 2020Smart recovery decision-making for end-of-life products in the context of ubiquitous information and computational intelligence34 cited
    • 2018Optimal Line Design of New and Remanufactured Products: A Model for Maximum Profit and Market Share with Environmental Consideration25 cited
    • 2023Big data analytics in flexible supply chain networks17 cited
    • 2020A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making13 cited
    • 2024D3 framework: An evidence-based data-driven design framework for new product service development11 cited
    • 2021Data Mining in Product Portfolio and Variety Management – Literature Review on Use Cases and Research Potentials6 cited