International Journal of Uncertainty Fuzziness and Knowledge-Based Systems最新文献_第5页

Foreword: Special Issue on Advanced Decision Making Methods and Frameworks for Crisis Management During Pandemic Situations 前言:大流行情况下危机管理的高级决策方法和框架特刊

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-05-01 DOI: 10.1142/s0218488522020019

V. G. Díaz, Jerry Chun‐wei Lin, Juan Antonio Morente Molinera

引用次数: 0

Radial Restricted Boltzmann Machines with Functional Neural Network for Classification of the Fake and Real News Analysis 基于功能神经网络的径向受限玻尔兹曼机真假新闻分类分析

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400025

V. Muthu Lakshmi, R. Radhika, G. Kalpana

引用次数: 0

Analysis on Prediction of Covid-19 with Machine Learning Algorithms 基于机器学习算法的Covid-19预测分析

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400049

R. Sathyaraj, R. Kanthavel, Luigi Pio Leonardo Cavaliere, Sumit Vyas, S. Maheswari, Ravi Gupta, M. Ramkumar Raja, R. Dhaya, M. Gupta, Sudhakar Sengan

{"title":"Analysis on Prediction of Covid-19 with Machine Learning Algorithms","authors":"R. Sathyaraj, R. Kanthavel, Luigi Pio Leonardo Cavaliere, Sumit Vyas, S. Maheswari, Ravi Gupta, M. Ramkumar Raja, R. Dhaya, M. Gupta, Sudhakar Sengan","doi":"10.1142/s0218488522400049","DOIUrl":"https://doi.org/10.1142/s0218488522400049","url":null,"abstract":"During the pandemic, the most significant reason for the deep concern for COVID-19 is that it spreads from individual to individual through contact or by staying close with the diseased individual. COVID-19 has been understood as an overall pandemic, and a couple of assessments is being performed using various numerical models. Machine Learning (ML) is commonly used in every field. Forecasting systems based on ML have shown their importance in interpreting perioperative effects to accelerate decision-making in the potential course of action. ML models have been used for long to define and prioritize adverse threat variables in several technology domains. To manage forecasting challenges, many prediction approaches have been used extensively. The paper shows the ability of ML models to estimate the amount of forthcoming COVID-19 victims that is now considered a serious threat to civilization. COVID-19 describes the comparative study on ML algorithms for predicting COVID-19, depicts the data to be predicted, and analyses the attributes of COVID-19 cases in different places. It gives an underlying benchmark to exhibit the capability of ML models for future examination.","PeriodicalId":50283,"journal":{"name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","volume":"255 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79647259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

G-Sep: A Deep Learning Algorithm for Detection of Long-Term Sepsis Using Bidirectional Gated Recurrent Unit G-Sep:用于双向门控循环单元检测长期脓毒症的深度学习算法

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400013

R. Rajmohan, T. Ananth Kumar, E. Golden Julie, Y. Harold Robinson, S. Vimal, Seifidine Kadry, R. G. Crespo

引用次数: 1

Minimizing Subtle Errors in Computing Information of TCAM By Partial 'N' Search Key Implementation 部分“N”搜索键实现最小化TCAM计算信息中的细微错误

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400098

K. Sakthi, P. Nirmal Kumar

引用次数: 0

Analyzing the Impact of Lockdown in Controlling Covid-19 Spread and Future Prediction 分析封锁对控制Covid-19传播的影响及未来预测

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400050

Mamoona Anam, Roy Setiawan, Sathiya Kumar Chinnappan, Nik Alif Amri Nik Hashim, Abolfazl Mehbodniya, C. Bhargava, Pardeep Kumar Sharma, K. Phasinam, V. Subramaniyaswamy, Sudhakar Sengan

{"title":"Analyzing the Impact of Lockdown in Controlling Covid-19 Spread and Future Prediction","authors":"Mamoona Anam, Roy Setiawan, Sathiya Kumar Chinnappan, Nik Alif Amri Nik Hashim, Abolfazl Mehbodniya, C. Bhargava, Pardeep Kumar Sharma, K. Phasinam, V. Subramaniyaswamy, Sudhakar Sengan","doi":"10.1142/s0218488522400050","DOIUrl":"https://doi.org/10.1142/s0218488522400050","url":null,"abstract":"COVID-19 outbreaks are the critical challenge to the administrative units of all worldwide nations. India is also more concerned about monitoring the virus’s spread to control its growth rate by stringent behaviour. The present COVID-19 situation has huge impact in India, and the results of various preventive measures are discussed in this paper. This research presents different trends and patterns of data sources of States that suffered from the second wave of COVID-19 in India until 3rd July 2021. The data sources were collected from the Indian Ministry of Health and Family Welfare. This work reacts particularly to many research activities to discover the lockdown effects to control the virus through traditional methods to recover and safeguard the pandemic. The second wave caused more losses in the economy than the first wave and increased the death rate. To avoid this, various methods were developed to find infected cases during the regulated national lockdown, but the infected cases still harmed unregulated incidents. The COVID-19 forecasts were made on 3rd July 2021, using exponential simulation. This paper deals with the methods to control the second wave giving various analyses reports showing the impact of lockdown effects. This highly helps to safeguard from the spread of the future pandemic.","PeriodicalId":50283,"journal":{"name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","volume":"33 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82588536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Analysis of Special Children Education Using Data Mining Approach 用数据挖掘方法分析特殊儿童教育

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400074

R. Dhanalakshmi, B. Muthukumar, R. Aroul canessane

引用次数: 1

Twitter Sentiment Analysis Using Social-Spider Lex Feature-Based Syntactic-Senti Rule Recurrent Neural Network Classification 基于社交蜘蛛Lex特征的句法- senti规则递归神经网络分类的Twitter情感分析

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400037

K. Anuratha, M. Parvathy

引用次数: 0

Predicting Corona Virus Affected Patients Using Supervised Machine Learning 使用监督机器学习预测冠状病毒感染患者

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400086

H. Benjamin Fredrick David, A. Suruliandi, S. Raja

{"title":"Predicting Corona Virus Affected Patients Using Supervised Machine Learning","authors":"H. Benjamin Fredrick David, A. Suruliandi, S. Raja","doi":"10.1142/s0218488522400086","DOIUrl":"https://doi.org/10.1142/s0218488522400086","url":null,"abstract":"The world is infected from the deadliest pandemic disease humankind has ever seen. Several medical practitioners have been encountered with the corona virus and are constantly losing their lives in the fight. Hence, the main objective of this research work is to characterize the clinical features of the patients and construct a novel dataset for machine learning to classify them accurately prior to treatment. The positive patients can be identified on many characteristics and the principle data for this research is considered on the basis of the exploratory analysis done on the various risk factors that is also associated with the mortality in the hospitals. As an outcome, this article presents a supervised machine learning model incorporating the insights, symptoms and classification of the corona virus infected person. The proposed model and the dataset are tested against six well known classifiers on various levels of cross folding and percentage splits. The proposed dataset is also tested against the actual patient records and was found that the model accurately categorizes them prior to their treatment. The experimental results for proposed techniques showed higher performance and better accuracy further creating an impact on then identification of corona virus patients.","PeriodicalId":50283,"journal":{"name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","volume":"30 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74914285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Visiting Indian Hospitals Before, During and After Covid 在Covid之前，期间和之后访问印度医院

IF 1.5 4区计算机科学

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems Pub Date : 2022-04-11 DOI: 10.1142/s0218488522400062

E. Pavithra, B. Janakiramaiah, L. V. Narasimha Prasad, D. Deepa, N. Jayapandian, Sathishkumar V E

{"title":"Visiting Indian Hospitals Before, During and After Covid","authors":"E. Pavithra, B. Janakiramaiah, L. V. Narasimha Prasad, D. Deepa, N. Jayapandian, Sathishkumar V E","doi":"10.1142/s0218488522400062","DOIUrl":"https://doi.org/10.1142/s0218488522400062","url":null,"abstract":"The prevailing COVID-19 situation has brought in temporary and permanent changes in the attitude and lifestyle of people. Starting from Hand sanitizers and face masks, it extends to online classrooms and work from home culture. In case of visiting hospitals and medications, people with pre-existing medical conditions and minor health issues tend to delay or avoid visiting hospitals due to fear of infection, which is dangerous. Further, people or patients tend to access several alternatives and precautions. The alternatives include home remedies, ayurvedic medication, yoga and meditation. On the other hand, hospitals are trying to adapt online consulting and telemedicine. Besides, Cancellation or delay of nonemergency surgeries became inevitable in the lockdown phase. This survey conducted among the people of Erode district, Tamilnadu to study the perception of people concerning visiting hospitals for health issues. The results show that fear of infection, financial and transportation difficulties are the major factors which affected people from visiting hospital. Also, changing trends like Telemedicine and home remedies are likely to be permanently opted by people. In Brief, the outcomes reveal the changing attitude of people towards medication and hospital visiting habits.","PeriodicalId":50283,"journal":{"name":"International Journal of Uncertainty Fuzziness and Knowledge-Based Systems","volume":"14 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85110289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3