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检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1863 条记录，以下是211-220 订阅

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Diabetes Prediction based on Supervised and Unsupervised learning Techniques - A Review 3

Diabetes Prediction based on Supervised and Unsupervised Lea...

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Sivaraman, M. Sumitha, J. Dr. Sns Rajalakshmi College of Arts and Science Department of Computer Science Tamil Nadu Coimbatore India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

Diabetes is a disorder that develops in the human body when blood glucose or sugar levels are extremely high. machine learning (ML) is subfield of Artificial Intelligence (AI) that is built on the idea that systems and machines will evaluate and interpret data, learn from it, and make a decision with no human participation. Medical fields that operate with massive amounts of data have recognized by the of machine learning technology. Health care systems can work more effectively and gain a competitive advantage by extracting insights from this data. The general goal of this study is to discover and observe the working and performance of various machine-learning algorithms. This paper work discusses the possibilities of employing machine-learning technology in healthcare. © 2022 IEEE.

关键词： Data mining

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Impact of machine learning in Digital Marketing applications 3

Impact of Machine Learning in Digital Marketing Applications

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3rd international Informatics and Software Engineering conference, IISEC 2022

作者： Gursoy, Gunes Varol, Asaf Varol, Serkan Maltepe University College of Engineering and Natural Sciences Dept. of Computer Engineering İstanbul Turkey The University of Chattanooga College of Engineering and Computer Science Dept. of Engineering Management and Technology ChattanoogaTN United States

ISBN: (数字)9781665459952

ISBN: (纸本)9781665459952

The devastating Covid 19 pandemic has shifted priorities in the business world to accommodate the new normal that the pandemic has caused. Digital marketing has become a necessity for corporations to keep up with the evolving needs of consumers. With the help of the emerging technologies, corporations have begun embracing tailored digital marketing applications that aim to attract and retain more consumers. The techniques or applications used by businesses to improve their marketing performance are consolidated and supported by artificial intelligence applications. In this study, we examine the significance of the marketing field and machine learning, as well as marketing techniques, artificial intelligence, and machine learning algorithms. As a result of the examinations, it has been shown how machine learning techniques and algorithms facilitate marketing processes, increase the profitability of businesses and it is very difficult to realize digital marketing without machine learning algorithms. © 2022 IEEE.

关键词： Marketing

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Predicting Crop on the basis of Climatic Parameters using machine learning Approaches 3

Predicting Crop on the basis of Climatic Parameters using Ma...

引用

3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Negi, Harendra Singh Dimri, Sushil Chandra Kumar, Bhawnesh Dobhal, Dinesh C. Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665462006

India as a country is largely dependent on agriculture. New techniques are being implemented by government and farmers for increasing crop production and crop yield. AI and machine learning are most popular technologies that are being used by government and big private firms for predictions in various sectors like agriculture, healthcare, auto mobile etc. The yield is dependent on factors like weather, fertilizer, pesticide, soil and rain. This article discusses about implementation of machine learning models in agriculture where we are predicting crop that is suitable for the soil at a particular place keeping in mind nutrients and weather of that place. This work will help farmers who are new and will guide them for showing crops by the help of machine learning, which is most advanced technologies to predicates the crop for future forecasting. © 2022 IEEE.

关键词： machine learning

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machine learning based Intelligent Health Monitoring System 3

Machine Learning based Intelligent Health Monitoring System

引用

3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Ainapure, Bharati Patrikar, Prajakta Mehta, Aanchal Jain, Aniket Shah, Sanika Vishwakarma University Department of Computer Pune India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

In today's unprecedented time, it is essential to stay one step ahead in the field of healthcare as well as health intelligence by detecting and determining health related problems beforehand and taking swift decisions. However, due to a hectic schedule, it is not always possible for people to go to a medical appointment in person. This may cause therapy to be delayed, and it may eventually become the source of serious health problems. Proposed machine learning based health monitoring system is an android-based smart application that will not only assist users in identifying an illness based on symptoms but will also allow them to communicate with a professional. When a patient enters his or her symptoms, the system uses machine learning and deep learning algorithms to diagnose the illness. The system will offer a list of doctors who specialize in similar conditions based on the disease that has been diagnosed. Users can also arrange an appointment with a doctor at a time and date that is convenient for them. Procuring consultations by utilizing the chatting is also possible. © 2022 IEEE.

关键词： Data mining

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A study on the application of named entity recognition in resume parsing 3

A study on the application of named entity recognition in re...

引用

3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Liang, Haifeng Chengdu University of Information Technology Shuangliu Chengdu610225 China

ISBN: (纸本)9781510661301

In recent years, with the development of machine learning as well as deep learning, named entity recognition has also been rapidly developed. Currently, with the huge saturation of the talent market, resulting in a dramatic increase in the number of resumes, it has become more difficult to screen resumes, and company personnel have taken on a huge burden of screening work. The application of named entity recognition on resume parsing can greatly shorten the time of resume screening and apply more time to the screening of target talents. Based on the problems faced by named entity recognition in resume parsing, this paper proposes traditional machine learning models HMM, CRF and deep learning model BiLSTM+CRF to solve them. After a series of experiments, the effectiveness of the proposed method is proved. © 2023 SPIE.

关键词： Deep learning

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Research on the Impact of MALL on Oral English Blended learning under the Background of "Internet Plus Education" : - Taking "FiF Oral English Training System" of iFLYTEK as an Example 3

Research on the Impact of MALL on Oral English Blended Learn...

引用

3rd international conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Du, Xiaoxuan Dalian Neusoft University of Information School of Foreign Languages Dalian China

ISBN: (纸本)9781665416665

Under the background of "Internet Plus Education", the Internet plays a more important role in oral English learning. With the rapid development of technology, the machine-aided learning has developed from computer assisted language learning (CALL) to the stage of mobile assisted language learning (MALL). At the same time, blended learning, which combines online and face-to-face learning, is also widely adopted. This paper makes use of contrast tests to analyze the pretest and posttest result statistics, aiming to research on the impact of MALL on oral English blended learning. © 2022 IEEE.

关键词： computer aided instruction

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Prediction of rainfall-type debris flow in Jiangjiagou based on LSTM-Attention 3

Prediction of rainfall-type debris flow in Jiangjiagou based...

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3rd international conference on computer Vision, Image and Deep learning and international conference on computer Engineering and applications, CVIDL and ICCEA 2022

作者： Gao, Yuan Li, Yingna Kunming University of Science and Technology College of Faculty of Information Engineering and Automation Kunming China Key Laboratory of Computer Technology Application of Yunnan Province Kunming China

ISBN: (纸本)9781665459112

Through the neural network model, the rainfall-type debris flow in Jiangjiagou is predicted. Based on seven meteorological factors with time series characteristics, such as daily rainfall, previous effective rainfall, ground temperature, and humidity, which have been screened by features, the Jiangjiagou rainfall debris flow prediction and early warning model based on LSTM-Attention is constructed. The results show that: (1) LSTM-Attention model is 0.02 higher than that of the Attention-LSTM model, and the prediction effect is better. (2) The prediction accuracy of LSTM-Attention model for Jiangjiagou rainfall-type debris flow can reach 0.88, which is 0.05, 0.07, 0.04, 0.25, 0.13 higher than that of LSTM model, RNN model, RNN-Attention model, SVM model, and BP model, respectively. Research results: It provides a new idea and method for the prediction and research of rainfall-type debris flow, which can be referenced by scholars. © 2022 IEEE.

关键词： Long short-term memory

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Research of Early Warning of Corporate Financial Crisis Based on machine learning Neural Network 3

Research of Early Warning of Corporate Financial Crisis Base...

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2022 3rd international conference on computer Information and Big Data applications, CIBDA 2022

作者： Zhao, Yanli Yang, Guang School of Business Administration Wuhan Business University Wuhan China School of Information and Safety Engineering Zhongnan University of Economics and Law Wuhan China

ISBN: (纸本)9783800758760

In order to predict the financial crisis more accurately, based on kernel principal component analysis (KPCA) and Multilayer Perceptron (MLP), a financial crisis early warning model is proposed. Firstly, to eliminate random noise in massive financial data, the KPCA is used to extract the key information of financial data. Secondly, the MLP is adopted to predict the financial crisis. Finally, compared with other traditional machine learning financial early warning methods, our proposed method obtains the best prediction capability. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Forecasting

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A Comparative Study of machine learning Algorithms for Photovoltaic Degradation Rate Prediction 3

A Comparative Study of Machine Learning Algorithms for Photo...

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Dhingra, Bhavya Tyagi, Shivam Tomar, Anuradha Netaji Subhas University of Technology Department of Electrical Engineering Delhi78 India Netaji Subhas University of Technology Department of Computer Science Delhi78 India Netaji Subhas University of Technology Department of Inst. and Control Engg. Delhi78 India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Solar energy is the most versatile, harmless, and non-exhaustive energy present in nature because of this, the number of photovoltaic modules that have been integrated into the electrical grid is increasing every day. As a result, reliable forecasting of falling power output over the period of time is required for an acceptable return on investment made for these interactions, to estimate the power delivered to the power system by these photovoltaic modules, photovoltaic degradation rates must be known. In this study degradation rates of photovoltaic modules are estimated using the application of nine machine learning models and the effectiveness of these models is compared in order to determine which model is most efficient. All the models are tested on various evaluation metrics like mean absolute error, root mean squared error, and mean percentage error for an unbiased evaluation, and the run time of these models is also calculated and compared to determine the overall efficiency of the models. © 2022 IEEE.

关键词： machine learning

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AgriCare: An Android application for Detection of Paddy Diseases 3

AgriCare: An Android Application for Detection of Paddy Dise...

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3rd international conference for Emerging Technology, INCET 2022

作者： Talreja, Rounak Jawrani, Varsha Watwani, Bhajan Sengupta, Sharmila Rohera, Prium Raghuwanshi, K.S. Vesit Dept. of Computer Engineering Mumbai India Agricultural Research Station Lonavala India

ISBN: (纸本)9781665494991

Agriculture is a significant part of India's economy being one of the main sources of living. Paddy plant is one of the most important food crops of India covering about one-fourth of the total cropped area. Although having the potential in the market, India's lower paddy crop productivity/hector and higher cost of production is a major concern for farmers. The low yield can be addressed by designing a system that helps farmers identify and predict diseases in the paddy crops. There are so many types of paddy diseases. It is very difficult to manually identify appropriate properties for distinguishing different types of crop diseases. So an android app will help farmers to identify and detect a paddy plant disease using images of the disease-infected paddy crop based on machine learning image processing techniques. © 2022 IEEE.

关键词： Crops

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