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An Analysis of the Development of Modular Building Design Elements to Improve Thermal Performance of a Representative High Rise Residential Estate in the Coastline City of Famagusta, Cyprus. (2022). Altan, Hasim ; Ozarisoy, Bertug.
In: Sustainability.
RePEc:gam:jsusta:v:14:y:2022:i:7:p:4065-:d:782571.

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  17. Developing a common approach for classifying building stock energy models. (2020). Laverge, J ; Langevin, J ; Federico, F ; Ebrahimigharehbaghi, S ; Mata, E ; Fennell, P ; Nageli, C ; Sandberg, N ; Camarasa, C ; van Hove, M ; Jakob, M ; Delghust, M ; Webster, J ; Reyna, J L.
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  18. A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings. (2020). Danov, Stoyan ; Cipriano, Jordi ; Mor, Gerard ; Grillone, Benedetto ; Sumper, Andreas.
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  19. Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings. (2020). Luo, X J ; Akinade, Olugbenga O ; Oyedele, Lukumon O ; Owolabi, Hakeem A ; Ahmed, Ashraf ; Ajayi, Anuoluwapo O.
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  20. Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive. (2020). Cellura, Maurizio ; Camilleri, Liberato ; Guarino, Francesco ; Gatt, Damien ; Yousif, Charles.
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  21. On the assessment and control optimisation of demand response programs in residential buildings. (2020). de Rosa, Mattia ; Dettorre, Francesco ; Pallonetto, Fabiano ; Finn, Donal P.
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  23. A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour. (2020). Li, Xinyi ; Yao, Runming.
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  24. Nature-inspired metaheuristic ensemble model for forecasting energy consumption in residential buildings. (2020). Chou, Jui-Sheng ; Luong, Duc-Long ; Tran, Duc-Hoc.
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  25. The impact of political instruments on building energy retrofits: A risk-integrated thermal Energy Hub approach. (2020). Trankler, Timm ; Wenninger, Simon ; Rockstuhl, Sebastian ; Ahlrichs, Jakob.
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  26. Are Pakistani homebuyers ready to adopt sustainable housing? An insight into their willingness to pay. (2020). Ali, Tauha Hussain ; Javid, Rana Asad ; Thaheem, Muhammad Jamaluddin.
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  27. Artificial neural network structure optimisation for accurately prediction of exergy, comfort and life cycle cost performance of a low energy building. (2020). Kerdan, Ivan Garcia ; Galvez, David Morillon.
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  28. A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making. (2020). Shamsi, Mohammad Haris ; Bohacek, Mark ; Purcell, Karl ; Odonnell, James ; Mangina, Eleni ; Hoare, Cathal ; Ali, Usman.
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  29. Data-driven estimation of building energy consumption with multi-source heterogeneous data. (2020). Pan, Yue ; Zhang, Limao.
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  30. A data-driven approach to optimize urban scale energy retrofit decisions for residential buildings. (2020). Shamsi, Mohammad Haris ; Bohacek, Mark ; Purcell, Karl ; Odonnell, James ; Mangina, Eleni ; Hoare, Cathal ; Ali, Usman.
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  31. Optimal control of demand flexibility under real-time pricing for heating systems in buildings: A real-life demonstration. (2020). Zeiler, Wim ; Li, Rongling ; Finck, Christian.
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  32. A novel improved model for building energy consumption prediction based on model integration. (2020). Feng, Wei ; Lu, Shilei ; Wang, Ran.
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  33. Statistical investigations of transfer learning-based methodology for short-term building energy predictions. (2020). Tseng, Yen Chieh ; Ma, Jie ; Wang, Jiayuan ; Xiao, FU ; Lee, Dasheng ; Fan, Cheng ; Sun, Yongjun.
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  34. A hybrid model for building energy consumption forecasting using long short term memory networks. (2020). Somu, Nivethitha ; Ramamritham, Krithi ; Raman, Gauthama.
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  36. Framework for emulation and uncertainty quantification of a stochastic building performance simulator. (2020). Coors, V ; Wate, P ; Iglesias, M ; Robinson, D.
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  37. Investigation on transient energy consumption of cold storages: Modeling and a case study. (2019). Shao, Shuangquan ; Tian, Shen ; Liu, Bin.
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  38. Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control. (2019). Wakui, Tetsuya ; Yokoyama, Ryohei ; Sawada, Kento ; Aki, Hirohisa.
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  39. Investigating structural and occupant drivers of annual residential electricity consumption using regularization in regression models. (2019). Satre-Meloy, Aven.
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  40. Thermal performance of an active thermoelectric ventilation system applied for built space cooling: Network model and finite time thermodynamic optimization. (2019). Cai, Yang ; Ding, Wen-Tao ; Wang, Lei ; Zhao, Fu-Yun ; Liu, DI.
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  41. An integrated data-driven framework for urban energy use modeling (UEUM). (2019). Azari, Rahman ; Abbasabadi, Narjes ; Heidarinejad, Mohammad ; Ashayeri, Mehdi ; Stephens, Brent.
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  42. Framework for estimation of the direct rebound effect for residential photovoltaic systems. (2019). Oliver, Matthew ; Toroghi, Shahaboddin H.
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  43. A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management. (2019). Song, Mengjie ; Wang, Jiayuan ; Xiao, FU ; Fan, Cheng.
    In: Applied Energy.
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  44. Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm. (2019). Liu, Ziang ; Xu, Xiaodong ; Wang, Wei ; Hong, Tianzhen ; Chen, Jiayu.
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  45. Water withdrawal and consumption reduction for electrical energy generation systems. (2019). Otieno, Wilkistar ; Nouri, Narjes ; Seifoddini, Hamid ; Balali, Farhad ; Nasiri, Adel.
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  46. Vector field-based support vector regression for building energy consumption prediction. (2019). Mu, Yunfei ; Lv, Shilei ; Wang, Jiajun ; Jia, Hongjie ; Zhong, Hai.
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  47. Deep learning-based feature engineering methods for improved building energy prediction. (2019). Sun, Yongjun ; Zhao, Yang ; Song, Mengjie ; Wang, Jiayuan ; Fan, Cheng.
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  48. A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses. (2019). Mao, Ning ; Dong, Jin ; Munk, Jeffrey ; Xiao, FU ; Fan, Cheng ; Cui, Borui ; Kuruganti, Teja.
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  49. A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning. (2019). Li, Zhengdao ; Wang, Jiayuan ; Xiao, FU ; Liu, Chengliang ; Fan, Cheng ; Yan, Chengchu.
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  50. A D-vine copula quantile regression approach for the prediction of residential heating energy consumption based on historical data. (2019). Trankler, Timm ; Niemierko, Rochus ; Toppel, Jannick.
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  51. A review of uncertainty analysis in building energy assessment. (2018). Feng, Xiaohang ; Tian, Wei ; de Wilde, Pieter ; Augenbroe, Godfried ; Yan, DA ; Park, Cheol Soo ; Li, Zhanyong ; Heo, Yeonsook.
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    RePEc:eee:rensus:v:93:y:2018:i:c:p:285-301.

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  52. Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders. (2018). Chou, Jui-Sheng ; Tran, Duc-Son.
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  53. Data-driven heating and cooling load predictions for non-residential buildings based on support vector machine regression and NARX Recurrent Neural Network: A comparative study on district scale. (2018). Frisch, J ; Koschwitz, D ; van Treeck, C.
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    RePEc:eee:energy:v:165:y:2018:i:pa:p:134-142.

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  54. Potential of three variant machine-learning models for forecasting district level medium-term and long-term energy demand in smart grid environment. (2018). Ahmad, Tanveer ; Chen, Huanxin.
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    RePEc:eee:energy:v:160:y:2018:i:c:p:1008-1020.

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  55. Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings. (2018). Brandi, Silvio ; Piscitelli, Marco Savino ; Chicco, Gianfranco ; Grassi, Daniele ; Capozzoli, Alfonso.
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    RePEc:eee:energy:v:157:y:2018:i:c:p:336-352.

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  56. Machine learning-based thermal response time ahead energy demand prediction for building heating systems. (2018). Huang, Ronggeng ; Wang, Jiangyu ; Liu, Jiangyan ; Chen, Huanxin ; Xu, Chengliang ; Guo, Yabin.
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