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A Multi-Step Time-Series Clustering-Based Seq2Seq LSTM Learning for a Single Household Electricity Load Forecasting. (2022). Masood, Zaki ; Choi, Yonghoon ; Gantassi, Rahma.
In: Energies.
RePEc:gam:jeners:v:15:y:2022:i:7:p:2623-:d:786419.

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  1. Attention enhanced dual stream network with advanced feature selection for power forecasting. (2025). Khan, Taimoor ; Choi, Chang.
    In: Applied Energy.
    RePEc:eee:appene:v:377:y:2025:i:pc:s0306261924019470.

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  2. Ultra short term power load forecasting based on the fusion of Seq2Seq BiLSTM and multi head attention mechanism. (2024). Guo, Cheng ; Gou, Yuanfang ; Qin, Risheng.
    In: PLOS ONE.
    RePEc:plo:pone00:0299632.

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  39. Hybrid genetic algorithm method for efficient and robust evaluation of remaining useful life of supercapacitors. (2020). Wang, Yanan ; Kang, LE ; Pang, Jinbo ; Peng, Fei ; Zhou, Yanting.
    In: Applied Energy.
    RePEc:eee:appene:v:260:y:2020:i:c:s0306261919318562.

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  40. Short-term power prediction of photovoltaic power station based on long short-term memory-back-propagation. (2019). Kuang, Liang ; Zhu, Erxi ; Pi, Dechang ; Hua, Chi.
    In: International Journal of Distributed Sensor Networks.
    RePEc:sae:intdis:v:15:y:2019:i:10:p:1550147719883134.

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  41. Deep Long Short-Term Memory: A New Price and Load Forecasting Scheme for Big Data in Smart Cities. (2019). Wadud, Zahid ; Mujeeb, Sana ; Javaid, Nadeem ; Afzal, Muhammad Khalil ; Ilahi, Manzoor ; Ishmanov, Farruh.
    In: Sustainability.
    RePEc:gam:jsusta:v:11:y:2019:i:4:p:987-:d:205948.

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  42. Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance. (2019). Haider, Syed Irtaza ; Alhussein, Musaed ; Aurangzeb, Khursheed.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:8:p:1487-:d:224240.

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  43. Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting. (2019). Bouktif, Salah ; Serhani, Mohamed Adel ; Ouni, Ali ; Fiaz, Ali.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:1:p:149-:d:194483.

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  44. Short-Term Load Forecasting for a Single Household Based on Convolution Neural Networks Using Data Augmentation. (2019). Wi, Young-Min ; Acharya, Shree Krishna ; Lee, Jaehee.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:18:p:3560-:d:268046.

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  45. Long-Term Demand Forecasting in a Scenario of Energy Transition. (2019). Sanchez-Duran, Rafael ; Barbancho, Julio ; Luque, Joaquin.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:16:p:3095-:d:256899.

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  46. Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches. (2019). Yang, Zhile ; Guo, Yuanjun ; Zhou, Yimin ; Wei, Yanjie ; Chang, Yan ; Feng, Shengzhong ; Mourshed, Monjur ; Zhu, Juncheng.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:14:p:2692-:d:248158.

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  47. District Heating Load Prediction Algorithm Based on Feature Fusion LSTM Model. (2019). Wang, Zhipan ; Pan, YU ; Lin, Tao ; Song, Jiancai ; Xue, Guixiang ; Qi, Chengying.
    In: Energies.
    RePEc:gam:jeners:v:12:y:2019:i:11:p:2122-:d:236771.

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  48. A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network. (2018). Zhan, Panpan ; Ma, Jian ; Zhang, Chunhong ; Tian, Chujie.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:12:p:3493-:d:190634.

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  49. Deep Learning Based on Multi-Decomposition for Short-Term Load Forecasting. (2018). Shin, Yong-June ; Kim, Seon Hyeog ; Lee, Gyul ; Kwon, Gu-Young.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:12:p:3433-:d:188862.

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  50. Designing, Developing, and Implementing a Forecasting Method for the Produced and Consumed Electricity in the Case of Small Wind Farms Situated on Quite Complex Hilly Terrain. (2018). Carutasu, George ; Cruau, George ; Petroanu, Dana-Mihaela ; Pirjan, Alexandru.
    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:10:p:2623-:d:173257.

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