scholarly journals Reservoir inflow predicting model based on machine learning algorithm via multi‐model fusion: A case study of Jinshuitan river basin

2021 ◽  
Author(s):  
Wei Zhang ◽  
Hanyong Wang ◽  
Yemin Lin ◽  
Jianle Jin ◽  
Wenjuan Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
River Basin ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Predicting Model ◽  
Model Fusion ◽  
Model Based ◽  
Reservoir Inflow

Twitter Users' Classification Based on Interest

2020 ◽  
Vol 10 (1) ◽  
pp. 1-12
Author(s):  
Noura A. AlSomaikhi ◽  
Zakarya A. Alzamil
Keyword(s):  
Machine Learning ◽  
Experimental Study ◽  
Knowledge Sharing ◽  
Naive Bayes ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Software System ◽  
Web Based ◽  
Twitter Users

Microblogging platforms, such as Twitter, have become a popular interaction media that are used widely for different daily purposes, such as communication and knowledge sharing. Understanding the behaviors and interests of these platforms' users become a challenge that can help in different areas such as recommendation and filtering. In this article, an approach is proposed for classifying Twitter users with respect to their interests based on their Arabic tweets. A Multinomial Naïve Bayes machine learning algorithm is used for such classification. The proposed approach has been developed as a web-based software system that is integrated with Twitter using Twitter API. An experimental study on Arabic tweets has been investigated on the proposed system as a case study.

Cooking Procedure Recognition and Support by Ubiquitous Sensors

2009 ◽  
Vol 21 (4) ◽  
pp. 498-506 ◽  
Author(s):  
Sho Murakami ◽  
◽  
Takuo Suzuki ◽  
Akira Tokumasu ◽  
Yasushi Nakauchi
Keyword(s):  
Machine Learning ◽  
Markov Model ◽  
User Behavior ◽  
Learning Algorithm ◽  
Experimental Results ◽  
Prediction Algorithm ◽  
Machine Learning Algorithm ◽  
Behavior Prediction ◽  
Model Based ◽  
Sensor Information

This paper proposes cooking support using ubiquitous sensors. We developed a machine learning algorithm that recognizes cooking procedures by taking into account widely varying sensor information and user behavior. To provide appropriate instructions to users, we developed a Markov-model-based behavior prediction algorithm. Using these algorithms, we developed cooking support automatically displaying cooking instruction videos based on user progress. Experiments and experimental results confirmed the feasibility of our proposed cooking support.

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