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Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods. (2018). Suryanarayana, Gowri ; Johansson, Christian ; Aleksiejuk, Piotr ; Geysen, Davy ; Lago, Jesus.
In: Energy.
RePEc:eee:energy:v:157:y:2018:i:c:p:141-149.

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    RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123013149.

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  2. Probabilistic spatiotemporal forecasting of wind speed based on multi-network deep ensembles method. (2023). Qu, Yuhua ; Shen, Qin ; Liu, Shuai ; Qin, Hui ; Wang, Yun ; Zhou, Jianzhong.
    In: Renewable Energy.
    RePEc:eee:renene:v:209:y:2023:i:c:p:231-247.

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  3. The data-based adaptive graph learning network for analysis and prediction of offshore wind speed. (2023). Yu, Jie ; Xu, Lingyu ; Li, Zhuolin ; Ren, Yuting.
    In: Energy.
    RePEc:eee:energy:v:267:y:2023:i:c:s0360544222034776.

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  4. A novel method for forecasting time series based on directed visibility graph and improved random walk. (2022). Xiao, Fuyuan ; Hu, Yuntong.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:594:y:2022:i:c:s0378437122000978.

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  5. A physics-inspired neural network model for short-term wind power prediction considering wake effects. (2022). Li, BO ; Shi, Ke-Zhong ; Guo, Nai-Zhi ; Xu, Jian-Zhong ; Zhang, Zi-Liang ; Wu, Hong-Hui ; Qi, Liang-Wen.
    In: Energy.
    RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222020989.

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  6. Interpretable temporal-spatial graph attention network for multi-site PV power forecasting. (2022). Carrillo, Rafael E ; Alet, Pierre-Jean ; Schubnel, Baptiste ; Simeunovi, Jelena ; Frossard, Pascal.
    In: Applied Energy.
    RePEc:eee:appene:v:327:y:2022:i:c:s0306261922013848.

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  7. Optimisation modelling tools and solving techniques for integrated precinct-scale energy–water system planning. (2022). Stewart, Rodney A ; Bertone, Edoardo ; de Oliveira, Glauber Cardoso.
    In: Applied Energy.
    RePEc:eee:appene:v:318:y:2022:i:c:s0306261922005578.

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  8. GPU accelerated power flow calculation of integrated electricity and heat system with component-oriented modeling of district heating network. (2022). Liu, Xinglei ; Chen, Zhang.
    In: Applied Energy.
    RePEc:eee:appene:v:305:y:2022:i:c:s0306261921011594.

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  9. Graph optimization neural network with spatio-temporal correlation learning for multi-node offshore wind speed forecasting. (2021). Yu, Jie ; He, Xiaoyu ; Xu, Lingyu ; Geng, Xiulin.
    In: Renewable Energy.
    RePEc:eee:renene:v:180:y:2021:i:c:p:1014-1025.

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  10. Hybrid wind speed forecasting model based on multivariate data secondary decomposition approach and deep learning algorithm with attention mechanism. (2021). Feng, Ruijun ; Zhang, Wenyu ; Xiao, Jiuhong ; Chen, Yong.
    In: Renewable Energy.
    RePEc:eee:renene:v:174:y:2021:i:c:p:688-704.

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  11. A review of wind speed and wind power forecasting with deep neural networks. (2021). Zhang, Lingjun ; Liu, Fang ; Zou, Runmin ; Wang, Yun.
    In: Applied Energy.
    RePEc:eee:appene:v:304:y:2021:i:c:s0306261921011053.

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  12. High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution. (2020). Schubnel, Baptiste ; Leblanc, Martin ; Carrillo, Rafael E ; Alet, Pierre-Jean ; Topfel, Cyril ; Langou, Renaud.
    In: Energies.
    RePEc:gam:jeners:v:13:y:2020:i:21:p:5763-:d:439556.

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  13. Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis. (2020). Tassinari, P ; Torreggiani, D ; Barbaresi, A ; Gholami, M.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:132:y:2020:i:c:s1364032120303270.

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  14. Research and Application of a Novel Hybrid Model Based on a Deep Neural Network Combined with Fuzzy Time Series for Energy Forecasting. (2019). Ni, Kailai ; Wang, Jianzhou ; Wei, Danxiang ; Tang, Guangyu.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:18:p:3588-:d:268869.

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  15. Residential load forecasting using wavelet and collaborative representation transforms. (2019). Ghassemian, Hassan ; Imani, Maryam.
    In: Applied Energy.
    RePEc:eee:appene:v:253:y:2019:i:c:86.

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  16. Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods. (2018). Suryanarayana, Gowri ; Johansson, Christian ; Aleksiejuk, Piotr ; Geysen, Davy ; Lago, Jesus.
    In: Energy.
    RePEc:eee:energy:v:157:y:2018:i:c:p:141-149.

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  17. Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving. (2018). Guo, Yabin ; Ahmad, Tanveer ; Liu, Jiangyan ; Huang, Ronggeng ; Wang, Jiangyu ; Chen, Huanxin ; Tan, Zehan.
    In: Applied Energy.
    RePEc:eee:appene:v:225:y:2018:i:c:p:732-745.

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  18. Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms. (2018). Lago, Jesus ; de Schutter, Bart ; de Ridder, Fjo.
    In: Applied Energy.
    RePEc:eee:appene:v:221:y:2018:i:c:p:386-405.

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  19. Do order imbalances predict Chinese stock returns? New evidence from intraday data. (2015). Narayan, Seema ; Westerlund, Joakim.
    In: Pacific-Basin Finance Journal.
    RePEc:eee:pacfin:v:34:y:2015:i:c:p:136-151.

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  20. Inside the Crystal Ball: New Approaches to Predicting the Gasoline Price at the Pump. (2015). Kilian, Lutz ; Baumeister, Christiane ; Lee, Thomas K.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:10362.

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  21. Time-series model forecasts and structural breaks: evidence from Spanish pre-EMU interest rates. (2008). Robles Fernandez, M. Dolores ; Robles-Fernandez, Dolores M. ; Fernandez-Serrano, Jose Luis.
    In: Applied Economics.
    RePEc:taf:applec:v:40:y:2008:i:13:p:1707-1721.

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  22. Forecasting Random Walks Under Drift Instability. (2008). Pesaran, M ; Pick, Andreas.
    In: Cambridge Working Papers in Economics.
    RePEc:cam:camdae:0814.

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  23. Short-Run Italian GDP Forecasting and Real-Time Data. (2005). Golinelli, Roberto ; Parigi, Giuseppe .
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:5302.

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  24. Land Inequality and the Origin of Divergence and Overtaking in the Growth Process: Theory and Evidence. (2004). Vollrath, Dietrich ; Moav, Omer ; Galor, Oded.
    In: Working Papers.
    RePEc:bro:econwp:2003-04.

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  25. Modelling the Yield Curve with Orthonomalised Laguerre Polynomials: An Intertemporally Consistent Approach with an Economic Interpretation. (2003). Krippner, Leo.
    In: Working Papers in Economics.
    RePEc:wai:econwp:03/01.

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  26. Choosing the Best Volatility Models:The Model Confidence Set Approach. (2003). Nason, James ; Lunde, Asger ; Hansen, Peter.
    In: Working Papers.
    RePEc:bro:econwp:2003-05.

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  27. Testing the Significance of Calendar Effects. (2003). Hansen, Peter.
    In: Working Papers.
    RePEc:bro:econwp:2003-03.

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  28. Long-Memory Forecasting of U.S. Monetary Indices. (2003). Barkoulas, John ; Baum, Christopher.
    In: Boston College Working Papers in Economics.
    RePEc:boc:bocoec:558.

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  29. Nonlinear stochastic trends and economic fluctuations. (2002). Camacho, Maximo.
    In: Computing in Economics and Finance 2002.
    RePEc:sce:scecf2:274.

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  30. Predicting the Equity Premium With Dividend Ratios. (2002). welch, ivo ; Goyal, Amit.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:8788.

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  31. Can Demography Improve Inflation Forecasts? The Case of Sweden. (2002). Bruer, Mattias.
    In: Working Paper Series.
    RePEc:hhs:uunewp:2002_004.

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  32. How well do monetary fundamentals forecast exchange rates?. (2002). Sarno, Lucio ; Neely, Christopher.
    In: Review.
    RePEc:fip:fedlrv:y:2002:i:sep:p:51-74:n:v.84no.5.

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  33. Priors from general equilibrium models for VARs. (2002). Schorfheide, Frank ; Del Negro, Marco.
    In: FRB Atlanta Working Paper.
    RePEc:fip:fedawp:2002-14.

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  34. On Out-of-Sample Statistics for Time-Series. (2002). Nadeau, Claude ; Bengio, Yoshua ; Gingras, Franois.
    In: CIRANO Working Papers.
    RePEc:cir:cirwor:2002s-51.

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  35. Estimated DGE Models and Forecasting Accuracy: A Preliminary Investigation with Canadian Data. (2002). Moran, Kevin ; Dolar, Veronika.
    In: Staff Working Papers.
    RePEc:bca:bocawp:02-18.

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  36. The Composite Index of Leading Economic Indicators: How to Make It More Timely. (2001). Ozyildirim, Ataman ; McGuckin, Robert H. ; Zarnowitz, Victor.
    In: NBER Working Papers.
    RePEc:nbr:nberwo:8430.

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  37. How to Beat the Random Walk. (2001). Alexius, Annika.
    In: Working Paper Series.
    RePEc:hhs:fiefwp:0175.

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  38. Modelling the Impact of Overnight Surprises on Intra-daily Stock Returns. (2001). Hong, Yongmiao ; Gallo, Giampiero ; Lee, Tae-Why.
    In: Econometrics Working Papers Archive.
    RePEc:fir:econom:wp2001_03.

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  39. Forecasting with a real-time data set for macroeconomists. (2001). Croushore, Dean ; Stark, Tom.
    In: Working Papers.
    RePEc:fip:fedpwp:01-10.

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  40. DUMB AND DUMBER EXPLANATIONS FOR EXCHANGE RATE DYNAMICS. (2001). Blomberg, Stephen.
    In: Journal of Applied Economics.
    RePEc:cem:jaecon:v:4:y:2001:n:2:p:187-216.

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  41. An Unbiased and Powerful Test for Superior Predictive Ability. (2001). Hansen, Peter.
    In: Working Papers.
    RePEc:bro:econwp:2001-06.

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  42. A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?. (2001). Lunde, Asger ; Hansen, Peter.
    In: Working Papers.
    RePEc:bro:econwp:2001-04.

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  43. Balassa-Samuelson Theory and Predictability of the US/UK Real Exchange Rate. (2000). KIM, CHUNG-HAN.
    In: International Economic Journal.
    RePEc:taf:intecj:v:14:y:2000:i:3:p:101-121.

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  44. THIS IS WHAT THE LEADING INDICATORS LEAD. (2000). Perez Quiros, Gabriel ; Camacho, Maximo ; Perez-Quiros, Gabriel.
    In: Computing in Economics and Finance 2000.
    RePEc:sce:scecf0:132.

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  45. The Accuracy of European Growth and Inflation Forecasts. (2000). Öller, Lars-Erik ; Barot, Bharat.
    In: Working Papers.
    RePEc:hhs:nierwp:0072.

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  46. Empirical Pricing Kernels. (2000). Rosenberg, Joshua ; Engle, Robert.
    In: New York University, Leonard N. Stern School Finance Department Working Paper Seires.
    RePEc:fth:nystfi:99-014.

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  47. A real-time data set for macroeconomists: does data vintage matter for forecasting?. (2000). Croushore, Dean ; Stark, Tom.
    In: Working Papers.
    RePEc:fip:fedpwp:00-6.

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  48. Does current-quarter information improve quarterly forecasts for the U.S. economy?. (2000). Stark, Tom.
    In: Working Papers.
    RePEc:fip:fedpwp:00-2.

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  49. Can out-of-sample forecast comparisons help prevent overfitting?. (2000). Clark, Todd.
    In: Research Working Paper.
    RePEc:fip:fedkrw:rwp00-05.

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  50. News and noise in G-7 GDP announcements. (2000). Wright, Jonathan ; Rogers, John ; Faust, Jon.
    In: International Finance Discussion Papers.
    RePEc:fip:fedgif:690.

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  51. Value of Sample Separation Information in a Sequential Probit Model: Another Look at SSAs Disability Determination Process. (2000). Lahiri, Kajal ; Wixon, Bernard ; Gao, Chuanming .
    In: Econometric Society World Congress 2000 Contributed Papers.
    RePEc:ecm:wc2000:0340.

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  52. Tests of Equal Forecast Accuracy and Encompassing for Nested Models. (2000). McCracken, Michael ; Clark, Todd.
    In: Econometric Society World Congress 2000 Contributed Papers.
    RePEc:ecm:wc2000:0319.

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  53. Tests of Equal Forecast Accuracy and Encompassing for Nested Models. (1999). McCracken, Michael ; Clark, Todd.
    In: Computing in Economics and Finance 1999.
    RePEc:sce:scecf9:1241.

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  54. Tests of equal forecast accuracy and encompassing for nested models. (1999). McCracken, Michael ; Clark, Todd.
    In: Research Working Paper.
    RePEc:fip:fedkrw:99-11.

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  55. Improving forecasts of the federal funds rate in a policy model. (1999). Tallman, Ellis ; Robertson, John.
    In: FRB Atlanta Working Paper.
    RePEc:fip:fedawp:99-3.

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  56. Norminal Exchange Rates and Monetary Fundamentals: Evidence from a Small Post-Bretton Woods Panel. (1998). Sul, Donggyu ; Mark, Nelson.
    In: Working Papers.
    RePEc:osu:osuewp:98-19.

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  57. Fundamentals of the Real Dollar-Pound Rate: 1871-1994. (1998). Mark, Nelson.
    In: Working Papers.
    RePEc:osu:osuewp:98-14.

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  58. The predictive content of the interest rate term spread for future economic growth. (1998). Dotsey, Michael.
    In: Economic Quarterly.
    RePEc:fip:fedreq:y:1998:i:sum:p:31-51.

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  59. Evaluating Density Forecasts. (1997). Tay, Anthony S ; Diebold, Francis ; Gunther, Todd A..
    In: Center for Financial Institutions Working Papers.
    RePEc:wop:pennin:97-37.

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  60. The Forecasting Ability of Correlations Implied in Foreign Exchange Options. (1997). Campa, Jose ; P. H. Kevin Chang, .
    In: NBER Working Papers.
    RePEc:nbr:nberwo:5974.

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  61. Evaluating density forecasts. (1997). Tay, Anthony S ; Diebold, Francis ; Gunther, Todd A..
    In: Working Papers.
    RePEc:fip:fedpwp:97-6.

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  62. Measuring predictability: theory and macroeconomic applications. (1997). Kilian, Lutz ; Diebold, Francis.
    In: Working Papers.
    RePEc:fip:fedpwp:97-23.

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  63. Cointegration and long-horizon forecasting. (1997). Diebold, Francis ; Christoffersen, Peter.
    In: Working Papers.
    RePEc:fip:fedpwp:97-14.

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  64. Optimal prediction under asymmetric loss. (1997). Diebold, Francis ; Christoffersen, Peter.
    In: Working Papers.
    RePEc:fip:fedpwp:97-11.

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  65. Evaluating forecasts of correlation using option pricing. (1997). BOYER, BRIAN H. ; Gibson, Michael S..
    In: International Finance Discussion Papers.
    RePEc:fip:fedgif:600.

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  66. Optimal Prediction Under Asymmetric Loss. (). Diebold, Francis ; Christoffersen, Peter.
    In: Home Pages.
    RePEc:wop:pennhp:_060.

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  67. Further Results on Forecasting and Model Selection Under Asymmetric Loss. (). Diebold, Francis.
    In: Home Pages.
    RePEc:wop:pennhp:_059.

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  68. Ex Post and Ex Ante Analysis of Provisional Data. (). Marcellino, Massimiliano ; Gallo, Giampiero.
    In: Working Papers.
    RePEc:igi:igierp:141.

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