| 1 |
A hybrid hourly natural gas demand forecasting method based on the integration of wavelet transform and enhanced Deep-RNN model
Su H, Zio E, Zhang JJ, Xu MJ, Li XY, Zhang ZJ
Energy, 178, 585, 2019 |
| 2 |
Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model
Panapakidis IP, Dagoumas AS
Energy, 118, 231, 2017 |
| 3 |
Breeder hybrid algorithm approach for natural gas demand forecasting model
Karadede Y, Ozdemir G, Aydemir E
Energy, 141, 1269, 2017 |
| 4 |
Forecasting the natural gas demand in China using a self-adapting intelligent grey model
Zeng B, Li C
Energy, 112, 810, 2016 |
| 5 |
Short-term natural gas demand prediction based on support vector regression with false neighbours filtered
Zhu L, Li MS, Wu QH, Jiang L
Energy, 80, 428, 2015 |
| 6 |
Appraisal of the support vector machine to forecast residential heating demand for the District Heating system based on the monthly overall natural gas consumption
Izadyar N, Ghadamian H, Ong HC, Moghadam Z, Tong CW, Shamshirband S
Energy, 93, 1558, 2015 |
| 7 |
Intelligent forecasting of residential heating demand for the District Heating System based on the monthly overall natural gas consumption
Izadyar N, Ong HC, Shamshirband S, Ghadamian H, Tong CW
Energy and Buildings, 104, 208, 2015 |
| 8 |
Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia
Potocnik P, Soldo B, Simunovic G, Saric T, Jeromen A, Govekar E
Applied Energy, 129, 94, 2014 |
| 9 |
The Asia Pacific natural gas market: Large enough for all?
Aguilera RF, Inchauspe J, Ripple RD
Energy Policy, 65, 1, 2014 |
| 10 |
On the demand for natural gas in urban China
Yu YH, Zheng XY, Han Y
Energy Policy, 70, 57, 2014 |
