2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)最新文献_第2页

Stock Prediction and analysis Using Supervised Machine Learning Algorithms 使用监督机器学习算法的股票预测和分析

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697162

Ajinkya Yelne, Dipti Theng

{"title":"Stock Prediction and analysis Using Supervised Machine Learning Algorithms","authors":"Ajinkya Yelne, Dipti Theng","doi":"10.1109/iccica52458.2021.9697162","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697162","url":null,"abstract":"Using Supervised Machine learning, our project is to analyzed and predict the stock value. As due to pandemic situation stock market trading is the most learned and become important activities to earn money as a second source of income in the people of India. The concept of predicting a stock's future worth is known as stock trading or stock prediction. Stock market is difficult to understand and to predict the value of stock. The majority of stock traders utilize various analytical techniques, as well as time series analysis, when seeking to make stock forecasts. So, we need a better tool to get out of this contemptuous situation and help the common man to make profit. In this research, we discuss a Machine Learning strategy that will be taught using publicly released stock data to build information, then using that information to make a valid prediction.For accuracy and prediction of stock Classification and Regression Algorithms are used with Kaggle dataset a machine learning technique comes under supervised learning that are Random Forest, Decision Tree, and Logistic Regression to predict stock prices for the given company previous year data, employing prices with daily trading prices. Python is the coding language used to anticipate the stock market using machine learning. Result come across that Regression model has more accuracy and can predict more accurate stock price.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130580461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Performance Prediction of Product/Person Using Real Time Twitter Tweets 使用实时Twitter Tweets进行产品/人员的性能预测

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697223

Devesh Bhangale, Snehal Poojary, Sameer Ahire, Priyanka Shingane

{"title":"Performance Prediction of Product/Person Using Real Time Twitter Tweets","authors":"Devesh Bhangale, Snehal Poojary, Sameer Ahire, Priyanka Shingane","doi":"10.1109/iccica52458.2021.9697223","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697223","url":null,"abstract":"Over a previous decade people have experienced an exponential boom in the usage of online resources in specific social media and microblogging internet site such as Twitter, Facebook, Instagram and YouTube. Many businesses and agencies has identified these sources as a wealthy mine of marketing information. On such platforms, massive quantities of records are produced (e.g.: 5000 tweets per 2d on twitter), this representing an chance for companies to check their social impact and people opinions towards their products, and even frequent people can additionally discover out what is a performance of a certain product or the overall performance of a particular political personality. In this project, we fetch the given number of tweets from users and classify it as Positive, Negative and Neutral by the usage of supervised machine learning approach. In this method we’re analyzing the Polarity and Subjectivity of the tweets and then later we’re using NLP to classify the raw records into records body which gets rid of the undesirable words from each of the tweets. Neutral words like ‘as, the, of’ are eliminated from the tweets. Using NLP, we get better results of the tweets, later we classify the tweets using classifying algorithms like Random Forest Classifier, Decision Tree Classifier, Logistic Regression, and Support Vector Classifier. Later it compares the result of tweets which had been analyzed before processing into NLP. We are also using Data Visualization for phrase frequencies, and for displaying a pie or bar chart of a variety of positive, negative and impartial tweets.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114212095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Arrhythmia Detection on ECG Signal Using Neural Network Approach 基于神经网络的心电信号心律失常检测

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697324

P. Yadav, S. Dorle, Rahul Agrawal

{"title":"Arrhythmia Detection on ECG Signal Using Neural Network Approach","authors":"P. Yadav, S. Dorle, Rahul Agrawal","doi":"10.1109/iccica52458.2021.9697324","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697324","url":null,"abstract":"The world has been shook by a rigorous pandemic covid-19 additionally it has accentuated a consequentiality on automating the health sectors from manually reading the reports to utilizing machine learning as an implement to getting the results of findings of sundry reports in an automated manner. There are many studies which have proved that the persons suffering from corona virus had optically discerned its effect on heart health. In rigorous cases it lead to cardiac apprehend proving it to be fatal for the patients. ECG (Electro cardiogram) is undertaken on patients to monitor their heart health; the ECG reports are then manually checked by medicos to conclude about heart health of a person. Cardiology is a study of heart and includes a variety of intricate diseases to be studied. This paper presents an efficient way of arrhythmia detection utilizing dataset which would be subsidiary for implementation of machine learning in this disease detection. Neural network has been utilized in the proposed work and is found to be 99% efficient thereby exhibiting a precise and tested method to further facilitate automation in this sector.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131288026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Challenges of Robot Assisted Teaching in Education Domain 机器人辅助教学在教育领域面临的挑战

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697252

Megha Gupta, Akshita Jain

引用次数: 0

Automatic Speech Analysis of Conversations for Dementia Detection Using LSTM and GRU 基于LSTM和GRU的会话语音自动分析用于痴呆检测

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697278

Neha Shivhare, Shanti Rathod, M. R. Khan

引用次数: 0

Model Proposal for a Yolo Objection Detection Algorithm based Social Distancing Detection System 基于Yolo目标检测算法的社交距离检测系统模型建议

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697212

Sudhir Sidhaarthan Balamurugan, Sanjay Santhanam, Anudeep Billa, R. Aggarwal, Nayan Varma Alluri

引用次数: 1

Fake News Detection Using XLNet Fine-Tuning Model 基于XLNet微调模型的假新闻检测

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697269

Ashok Kumar J, Tina Esther Trueman, E. Cambria

引用次数: 8

Glimpses of ICCICA 2021

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697124

引用次数: 0

Deep Neural Network-Based Classification and Diagnosis of Idiopathic Parkinsonism Disease 基于深度神经网络的特发性帕金森病分类与诊断

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697322

Anusha Chintam, Rajendra Kumar G, Anitha Rani J, Srilatha Yalamati, C. D

引用次数: 1

Delivery Robot Using GPS Technology 利用GPS技术的送货机器人

2021 International Conference on Computational Intelligence and Computing Applications (ICCICA) Pub Date : 2021-11-26 DOI: 10.1109/iccica52458.2021.9697159

Abdulraheem Shaik, N. Durga Naga Lakshmi, C. Srinivas

{"title":"Delivery Robot Using GPS Technology","authors":"Abdulraheem Shaik, N. Durga Naga Lakshmi, C. Srinivas","doi":"10.1109/iccica52458.2021.9697159","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697159","url":null,"abstract":"It is the service sector for any nation that offers the government the maximum income. This service industry comprises a broader range of services and every individual in the nation will be affected by any bad impacts on this sector. The covid pandemic has become a threat to good health and has created fear due to the spread of the virus and a serious impact on the economy and the livelihood of people in the country. Logistics and delivery are some of the areas badly affected by covid. Because this virus is a contagious disease and very quickly spreads to neighbours. The reduction of human interference in the delivery of goods was very important. This paper presents a delivery robot that can safely and securely deliver the goodseven for the virus affected persons since this robot is a virus free agent. The key features are face recognition, obstacle detection, live streaming, GPS tracking and we achieve these features using Raspberry Pi and Node MCU. The prototype we create is for small organizations such as colleges and hospitals where objects must be transported safely and securely. This robot can also be used to safely provide patients with medicines and food. This can be extended to a greater area and can be used to replace the normal human resources delivery system.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133646099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1