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Yupeng Yuan, Xiaoyu Wang, Liang Tong, Rui Yang and Boyang Shen
Various measures have been taken to improve ship energy efficiency while decreasing CO2 emissions. In this work, the navigation environment between Wuhan and Shanghai in China has been classified based on an improved K-means algorithm in order to realize...
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Xiaoyue Yang, Yi Yang, Shenghua Xu, Jiakuan Han, Zhengyuan Chai and Gang Yang
Geographically weighted regression (GWR) is a classical method for estimating nonstationary relationships. Notwithstanding the great potential of the model for processing geographic data, its large-scale application still faces the challenge of high comp...
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Jing Fu and Guangji Tong
As two influential countries in the global grain production and marketing system, China and Russia have increasingly strengthened their agricultural, economic, and trade cooperation. There are few papers that have considered trade relations from the pers...
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Jiaying Wang, Zhijie Zhao, Yang Liu and Yiqi Guo
With the flourishing development of the hotel industry, the study of customer satisfaction based on online reviews and data has become a new model. In this paper, customer reviews and ratings on Ctrip.com are used, and TF-IDF and K-means algorithms are u...
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Zezheng Zhao, Chunqiu Xia, Lian Chi, Xiaomin Chang, Wei Li, Ting Yang and Albert Y. Zomaya
From the perspective of energy providers, accurate short-term load forecasting plays a significant role in the energy generation plan, efficient energy distribution process and electricity price strategy optimisation. However, it is hard to achieve a sat...
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Julien Chevallier, Dominique Guégan and Stéphane Goutte
This paper focuses on forecasting the price of Bitcoin, motivated by its market growth and the recent interest of market participants and academics. We deploy six machine learning algorithms (e.g., Artificial Neural Network, Support Vector Machine, Rando...
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Daniel Ramos, Mahsa Khorram, Pedro Faria and Zita Vale
Energy efficiency topics have been covered by several energy management approaches in the literature, including participation in demand response programs where the consumers provide load reduction upon request or price signals. In such approaches, it is ...
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Christoph Hansknecht, Imke Joormann and Sebastian Stiller
The time-dependent traveling salesman problem (TDTSP) asks for a shortest Hamiltonian tour in a directed graph where (asymmetric) arc-costs depend on the time the arc is entered. With traffic data abundantly available, methods to optimize routes with res...
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Karshiev Sanjar, Olimov Bekhzod, Jaesoo Kim, Anand Paul and Jeonghong Kim
Accurate house price forecasts are very important for formulating national economic policies. In this paper, we offer an effective method to predict houses? sale prices. Our algorithm includes one-hot encoding to convert text data into numeric data, feat...
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Mochammad Agus Afrianto,Meditya Wasesa
Pág. 123 - 132
Background: Literature in the peer-to-peer accommodation has put a substantial focus on accommodation listings' price determinants. Developing prediction models related to the demand for accommodation listings is vital in revenue management because accur...
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