Variable step-size evolving participatory learning with kernel recursive least squares applied to gas prices forecasting in Brazil [0.03%]
基于核递归最小二乘的变步长进化参与学习在巴西天然气价格预测中的应用
Eduardo Ravaglia Campos Queiroz,Kaike Sa Teles Rocha Alves,Fernando Luiz Cyrino Oliveira et al.
Eduardo Ravaglia Campos Queiroz et al.
A prediction model is an indispensable tool in business, helping to make decisions, whether in the short, medium, or long term. In this context, the implementation of machine learning techniques in time series forecasting models has a notor...
FocusCovid: automated COVID-19 detection using deep learning with chest X-ray images [0.03%]
基于胸部X光图像的深度学习自动化COVID-19检测（FocusCovid）
Tarun Agrawal,Prakash Choudhary
Tarun Agrawal
COVID-19 is an acronym for coronavirus disease 2019. Initially, it was called 2019-nCoV, and later International Committee on Taxonomy of Viruses (ICTV) termed it SARS-CoV-2. On 30th January 2020, the World Health Organization (WHO) declare...
Deep recurrent Gaussian Nesterovs recommendation using multi-agent in social networks [0.03%]
基于多智能体的深度复发高斯尼埃沃推荐在社交网络中的应用研究
Vinita Tapaskar,Mallikarjun M Math
Vinita Tapaskar
Due to increasing volume of big data the high volume of information in Social Network put a stop to users from acquiring serviceable information intelligently so many recommendation systems have emerged. Multi-agent Deep Learning gains rapi...
Super-forecasting the 'technological singularity' risks from artificial intelligence [0.03%]
超前预测人工智能技术奇点的风险
Petar Radanliev,David De Roure,Carsten Maple et al.
Petar Radanliev et al.
This article investigates cybersecurity (and risk) in the context of 'technological singularity' from artificial intelligence. The investigation constructs multiple risk forecasts that are synthesised in a new framework for counteracting ri...
Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review [0.03%]
受自然启发的优化算法及其在多阈值图像分割中的意义：综述
Rebika Rai,Arunita Das,Krishna Gopal Dhal
Rebika Rai
Multilevel Thresholding (MLT) is considered as a significant and imperative research field in image segmentation that can efficiently resolve difficulties aroused while analyzing the segmented regions of multifaceted images with complicated...
Multivariate time series short term forecasting using cumulative data of coronavirus [0.03%]
基于累积数据的多元时间序列短期新冠肺炎预测模型
Suryanshi Mishra,Tinku Singh,Manish Kumar et al.
Suryanshi Mishra et al.
Coronavirus emerged as a highly contagious, pathogenic virus that severely affects the respiratory system of humans. The epidemic-related data is collected regularly, which machine learning algorithms can employ to comprehend and estimate v...
DBF-Net: a semi-supervised dual-task balanced fusion network for segmenting infected regions from lung CT images [0.03%]
DBF-Net：一种半监督双任务平衡融合网络用于分割肺部CT图像中的感染区域
Xiaoyan Lu,Yang Xu,Wenhao Yuan
Xiaoyan Lu
Accurate segmentation of infected regions in lung computed tomography (CT) images is essential to improve the timeliness and effectiveness of treatment for coronavirus disease 2019 (COVID-19). However, the main difficulties in developing of...
Vaccination and isolation based control design of the COVID-19 pandemic based on adaptive neuro fuzzy inference system optimized with the genetic algorithm [0.03%]
基于遗传算法优化自适应神经模糊推理系统的疫苗接种和隔离的COVID-19大流行控制设计
Zohreh Abbasi,Mohsen Shafieirad,Amir Hossein Amiri Mehra et al.
Zohreh Abbasi et al.
The study of the COVID-19 pandemic is of pivotal importance due to its tremendous global impacts. This paper aims to control this disease using an optimal strategy comprising two methods: isolation and vaccination. In this regard, an optimi...
Evolving fuzzy neural classifier that integrates uncertainty from human-expert feedback [0.03%]
融合人类专家反馈不确定性的进化模糊神经分类器
Paulo Vitor de Campos Souza,Edwin Lughofer
Paulo Vitor de Campos Souza
Evolving fuzzy neural networks are models capable of solving complex problems in a wide variety of contexts. In general, the quality of the data evaluated by a model has a direct impact on the quality of the results. Some procedures can gen...
Improving premise structure in evolving Takagi–Sugeno neuro-fuzzy classifiers [0.03%]
改进演化型Takagi-Sugeno神经模糊分类器中的前提结构
Abdullah Almaksour; Eric Anquetil
Abdullah Almaksour; Eric Anquetil