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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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Wenxiang Zhou, Sangwei Lu, Jinquan Huang, Muxuan Pan and Zhongguang Chen
Accurate component maps, which can significantly affect the efficiency, reliability and availability of aero-engines, play a critical role in aero-engine performance simulation. Unfortunately, the information of component maps is insufficient, leading to...
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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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Anna Bakurova, Olesia Yuskiv, Dima Shyrokorad, Anton Riabenko, Elina Tereschenko
Pág. 14 - 22
The subject of the research is the methods of constructing and training neural networks as a nonlinear modeling apparatus for solving the problem of predicting the energy consumption of metallurgical enterprises. The purpose of this work is to develop a ...
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Jegalakshimi Jewaratnam
Pág. 31
A multilayer feedforward neural network (MFNN) model is developed from the best performing backpropagation training algorithm among all eleven training algorithms. From experimental setup of microwave pyrolysis of oil palm fibre, the model utilized the i...
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