Deep reinforcement learning-based approach for rumor influence minimization in social networks [0.03%]
基于深度强化学习的社交网络谣言影响最小化方法研究
Jiajian Jiang,Xiaoliang Chen,Zexia Huang et al.
Jiajian Jiang et al.
Spreading malicious rumors on social networks such as Facebook, Twitter, and WeChat can trigger political conflicts, sway public opinion, and cause social disruption. A rumor can spread rapidly across a network and can be difficult to contr...
Short-term load forecasting system based on sliding fuzzy granulation and equilibrium optimizer [0.03%]
基于滑动模糊粒化和平衡优化器的短期负荷预测系统
Shoujiang Li,Jianzhou Wang,Hui Zhang et al.
Shoujiang Li et al.
Short-term electricity load forecasting is critical and challenging for scheduling operations and production planning in modern power management systems due to stochastic characteristics of electricity load data. Current forecasting models ...
A multi-robot deep Q-learning framework for priority-based sanitization of railway stations [0.03%]
一种基于优先级的火车站消毒多机器人深度Q学习框架
Riccardo Caccavale,Mirko Ermini,Eugenio Fedeli et al.
Riccardo Caccavale et al.
Sanitizing railway stations is a relevant issue, primarily due to the recent evolution of the Covid-19 pandemic. In this work, we propose a multi-robot approach to sanitize railway stations based on a distributed Deep Q-Learning technique. ...
Triple-kernel gated attention-based multiple instance learning with contrastive learning for medical image analysis [0.03%]
基于三核门注意机制的对比学习多重实例学习医学图像分析方法
Huafeng Hu,Ruijie Ye,Jeyan Thiyagalingam et al.
Huafeng Hu et al.
In machine learning, multiple instance learning is a method evolved from supervised learning algorithms, which defines a "bag" as a collection of multiple examples with a wide range of applications. In this paper, we propose a novel deep mu...
Sucheta Dawn,Sanghamitra Bandyopadhyay
Sucheta Dawn
Interval-valued data is an effective way to represent complex information where uncertainty, inaccuracy etc. are involved in the data space and they are worthy of taking into account. Interval analysis together with neural network has prove...
A sentiment analysis driven method based on public and personal preferences with correlated attributes to select online doctors [0.03%]
一种基于公共和私人偏好相关属性的在线医生选择的情感分析方法
Jian Wu,Guangyin Zhang,Yumei Xing et al.
Jian Wu et al.
This paper proposes a method to assist patients in finding the most appropriate doctor for online medical consultation. To do that, it constructs an online doctor selection decision-making method that considers the correlation attributes, i...
Intra-graph and Inter-graph joint information propagation network with third-order text graph tensor for fake news detection [0.03%]
基于三阶文本图张量的联合图内和图间信息传播网络假新闻检测方法
Benkuan Cui,Kun Ma,Leping Li et al.
Benkuan Cui et al.
Although the Internet and social media provide people with a range of opportunities and benefits in a variety of ways, the proliferation of fake news has negatively affected society and individuals. Many efforts have been invested to detect...
Adaptive model training strategy for continuous classification of time series [0.03%]
时间序列连续分类的自适应模型训练策略
Chenxi Sun,Hongyan Li,Moxian Song et al.
Chenxi Sun et al.
The classification of time series is essential in many real-world applications like healthcare. The class of a time series is usually labeled at the final time, but more and more time-sensitive applications require classifying time series c...
Classification framework for faulty-software using enhanced exploratory whale optimizer-based feature selection scheme and random forest ensemble learning [0.03%]
基于改进鲸鱼优化算法的特征选择方案和随机森林集成学习的软件缺陷分类框架
Majdi Mafarja,Thaer Thaher,Mohammed Azmi Al-Betar et al.
Majdi Mafarja et al.
Software Fault Prediction (SFP) is an important process to detect the faulty components of the software to detect faulty classes or faulty modules early in the software development life cycle. In this paper, a machine learning framework is ...
Feature selection of pre-trained shallow CNN using the QLESCA optimizer: COVID-19 detection as a case study [0.03%]
基于QLESCA优化器的预训练浅层CNN特征选择研究——以COVID-19检测为例
Qusay Shihab Hamad,Hussein Samma,Shahrel Azmin Suandi
Qusay Shihab Hamad
According to the World Health Organization, millions of infections and a lot of deaths have been recorded worldwide since the emergence of the coronavirus disease (COVID-19). Since 2020, a lot of computer science researchers have used convo...