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

共 1897 条记录，以下是431-440 订阅

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Research on Practical application and Optimization of Multi-Strategy Prediction Method Based on machine learning 3

Research on Practical Application and Optimization of Multi-...

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3rd international conference on computers, Information Processing and Advanced Education, CIPAE 2022

作者： He, Yuheng Yan, Menghan Wang, Shihong Xi'An Jiaotong University Faculty of Electronics and Information Engineering Shaanxi Xi'an710049 China School of Energy and Power Engineering Xi'An Jiaotong University Shaanxi Xi'an710049 China

ISBN: (纸本)9781665468121

In this paper, through the method of mathematical modeling, based on the practical application of the prediction model for research and mathematical modeling. First of all, based on literature research, this paper puts forward the basic prediction model and takes several high-precision algorithms based on statistics and machine learning as the sub-modules of the prediction model. We integrate multiple predictions provided by the sub-module and provide the final prediction through the integration. Then the prediction is regarded as a planning problem, and the index quantity of the optimal weight is introduced into the optimization objective to predict and get better results. © 2022 IEEE.

关键词： Forecasting

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Comparative Analysis of Rainfall Prediction Using machine learning and Deep learning Techniques 3

Comparative Analysis of Rainfall Prediction Using Machine Le...

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3rd international conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2022

作者： Chaudhary, Himanshi Mishra, Upendra Gupta, Arpita Singh, Amisha KIET Group of Institutions Department of Computer Science and Engineering Delhi-NCR Ghaziabad India

ISBN: (纸本)9781665482684

Since the previous decade, weather has changed rapidly, raising concerns about unpredictable rains. Humidity, pressure, wind, and temperature affect rainfall. Thus, studying such characteristics to predict rainfall is intriguing. machine learning and deep learning have simplified rainfall prediction, which is still under development. This study implements machine learning and deep learning models trained on 145460 rows and 25 characteristics. These models are tested on a test dataset using measures like accuracy and PRF score to determine the best model for rainfall prediction. Tuning each model's hyper-parameters improves results. A comparative study examined how different factors affect rainfall. This study covers preprocessing, feature engineering, model selection, and implementation. This work aims to offer an acceptable and accurate model for predicting rainfall in a web-app. This study compares machine learning and deep learning methods and provides easy access to them. © 2022 IEEE.

关键词： Rain

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Secure Online Book Resale Store System using machine learning 3

Secure Online Book Resale Store System using Machine Learnin...

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3rd international conference for Emerging Technology, INCET 2022

作者： Solanki, Yash Pattewar, Onkar Satpute, Saurav Suryawanshi, Pranav Lokhande, Meghana Pimpri Chinchwad College of Engineering Computer Engineering Pune India

ISBN: (纸本)9781665494991

Books are the indivisible part of the student's life. The demand for books will never decrease. When it comes to selling or buying a second-hand book, then it becomes a time-consuming task. Students who have to buy or sell the books have to go to the local shop and then they have to sell or buy the books at a lower price or higher price respectively. This scenario involves the involvement of a middle man (broker) which increases the price of books. The internet plays an important role in daily life. And the e-commerce industry has come into the spotlight in recent years. The local bookstore's space, time, and operation time are restricted. Because of that idea we provide services and convenience to people. The project aims to create one simple e-commerce website which contains the feature of selling and buying books online along with secure login using a hashing algorithm and recommendation system and Fake review detection using machine learning. © 2022 IEEE.

关键词： Websites

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U-NET and RCNN Ensembled Satellite Object Detection and Segmentation 3

U-NET and RCNN Ensembled Satellite Object Detection and Segm...

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3rd international conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Subhashini, G. Devi, Ajantha Niroshini Infantia, C. Karthi, M. Raghul, G. Shankar, S. Aravind St.Josephs Institute of Technology Chennai India AP3 Solutions Chennai India

ISBN: (纸本)9781665462167

Humans have always been curious to learn and explore new things and have achieved great things with that curiosity. "CURIOSITY IS THE WICK IN THE CANDLE OF learning,"said William Arthur Ward. With the advancing technologies and advancing human needs, automation has become a leading technology in the IT sector. In the year of 1959, the first ever man-made satellite, which could take pictures was launched for the purpose of observing our planet. This led to the widely used technology in the year 2022, The Satellite images play a very crucial role in the n day-to-day activities of humans. It's because of satellite imagery, the weather forecasting capabilities of humans have improved drastically. People can sleep without worrying about the next upcoming storm as it can be detected with the help of satellite imagery and machine learning algorithms. Thus, precautions for the same can be taken even before the storm is formed. GPS system is another widely used technology used for security and exploration purposes. Satellite imagery with GPS technology gave another revolutionary use for humans, such as live location tracking in a graphical map, detected and captured by satellites. An example of such an application is Google Maps. Google Maps use various type of satellite images and machine learning algorithms to automate the various operations for public use. With the help of these technologies, this article will give an overview that how satellite imagery helps us to detect objects from satellite images and further segment images from satellite images using machine learning algorithms like RCNN with RPN and U-NET. © 2023 IEEE.

关键词： Object detection

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Research on Enterprises' Response to Emergencies Based on machine learning 3

Research on Enterprises' Response to Emergencies Based on Ma...

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3rd international conference on computer Science and Management Technology, ICCSMT 2022

作者： Fan, Xiaonan Ren, Sainan Bao, Xiaona Lu, Xinyuan Dalian University of Technology School of Management Dalian China

ISBN: (纸本)9798350320404

The outbreak of the Corona Virus Disease 2019 quickly became an international and domestic public health emergency in the spotlight. Under the impact of the epidemic, private companies, especially offline businesses, have been hit hard. Therefore, private enterprises today need to pay more attention to enhancing "organizational resilience"and improving their resilience in the face of disruptions and disruptions caused by major emergencies. In this study, three machine learning methods are compared with traditional linear regression models to analyze the impact of organizational resilience on the response of small and medium-sized private enterprises to the epidemic. The same interview-based policy recommendations to boost the organizational resilience of small and medium-sized private enterprises in three northeastern provinces are proposed. The results of this survey show that the degree of influence of resilience commitment is the greatest among the main factors affecting the resilience of enterprises. According to the policy demands of enterprises, the government should help enterprises with difficulties in the epidemic by giving financial policy support, providing cost subsidies, and improving the national emergency management system. © 2022 IEEE.

关键词： machine learning

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Implementation of machine learning Based DDOS Attack Detection System 3

Implementation of Machine Learning Based DDOS Attack Detecti...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Bhargava, R. Pal Singh, Yash Narawade, Nawanath S Kalinga University Raipur India Parvatibai Genba Moze College of Engineering Pune India

ISBN: (纸本)9781665494991

The DoS/DDoS attacks are intended to bring the availability of the online services down to authentic users. The attacker seeds malware into the computers over the internet without the knowledge of the computer user/owner when they visit malicious websites, opening attachments from the unknown senders. DDoS attacks disrupt the availability of Web services for an indefinite amount of time by flooding the company's servers with false requests and refusing genuine ones, resulting in economic losses due to unavailability delivered services. The goal of this paper is to demonstrate how to detect prototype DDoS attacks using a supervised learning model based on Support Vector machines, which captures network traffic, filters HTTP headers, normalises the data based on operational variables such as rate of false positives, rate of false negatives, and rate of classification, and then sends the information to the appropriate training and testing sets. Various machine learning models, such as Navies Bayes, SVM, and suggested approaches based on Navies Bayes, were developed using the given characteristics. Bayes are a type of algorithm used to identify DDoS attacks. The results of our experiments suggest that Fuzzy c-means clustering is more accurate in recognising attacks. © 2022 IEEE.

关键词： Support vector machines

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Triplet Filter Based on Reinforcement learning for Relational Extraction 3

Triplet Filter Based on Reinforcement Learning for Relationa...

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3rd international conference on Pattern Recognition and machine learning, PRML 2022

作者： Dong, Zengbo Zhu, Jinhui Li, Hanren Xin, Rui Chen, Xi Song, Hui State Grid Hebei Electric Power CO.LTD Telecommunication Branch Shijiazhuang China Donghua University School of Computer Science and Technology Shanghai China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

The annotated data set for relational extraction task is usually generated through distant supervision which results in model performance degradation due to noise data introduced. Most of the existing works eliminate the noise data at the sentence level. This paper proposes a model based on reinforcement learning to achieve noise reduction at triplet level. The model identifies the noise triplets with the feature encoding of the sentence and entity pairs of the triplets which are updated through the feedback from the relation extraction module. The experimental results show that the model keeps the correct triplets while identifying the mislabeled ones in the sentence, and finally improves the performance of relational extraction models. © 2022 IEEE.

关键词： Extraction

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3rd international conference on Innovations in computer Science and Software Engineering, ICONICS 2022

3rd International Conference on Innovations in Computer Scie...

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3rd international conference on Innovations in computer Science and Software Engineering, ICONICS 2022

ISBN: (纸本)9781665461412

The proceedings contain 28 papers. The topics discussed include: experimentation for decentralized resource-based multi-pool mining in Ethereum blockchain;performance enhancement in agriculture sector based on image processing;frameworks, applications and challenges in streaming big data analytics: a review;prevention and safety strategies for road accidents by using evolutionary algorithms;intrusion detection using deep learning techniques;analyzing applicant’s pre-admission data and predicting applicant’s performance in pre-admission test using data mining techniques;quantum computing and machine learning algorithms - a review;real-time violence detection using deep learning techniques;a study on the e-commerce trends using data analysis;and a systematic review on the motivations of cyber-criminals and their attacking policies.

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Systematic Literature Review on application of Artificial Intelligence in Cancer Detection Using Image Processing 3

Systematic Literature Review on Application of Artificial In...

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3rd international conference on Artificial Intelligence and Data Sciences, AiDAS 2022

作者： Chandra, Giovanni Irisha, Kevina Diva Vica, Vivianit Indyca Suri, Puti Andam Syahputra, Muhammad Edo School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Having a low survival rate, cancer has become one of the deadliest diseases with complicated prognosis. In this matter, Artificial Intelligence (AI) is frequently used to aid humans due to the difficulties of cancer identification. Specifically, the use of AI in cancer detection and treatment uses two of its subclasses, machine learning and deep learning. Because those two subclasses can handle large amounts of data, their algorithms can support humans in making decisions that yield the best possible results with the least amount of risk. The purpose of this research is to find out the effectiveness of the Artificial Intelligence algorithm that is used in image processing to diagnose cancer and what is the most effective image processing algorithm for cancer diagnosis. The methods that are used in this research is Systematic Literature Review (SLR). As a result, Artificial Intelligence algorithms are sufficiently effective to be used in diagnosing cancer with image processing. Meanwhile, the most effective algorithm is CatBoost with AUC of 0.939 and Support Vector machine (SVM) with AUC of 0.934. © 2022 IEEE.

关键词： Image processing

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Research on the application of Paperless computerized College English Test Based on iTEST Platform 3

Research on the Application of Paperless Computerized Colleg...

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

作者： Shi, Qimeng Dalian Neusoft University of Information Department of English Dalian China

ISBN: (纸本)9781665416665

With the rapid development of educational technology and information technology, paperless computer-based test has become an inevitable means of college English teaching and assessment. Based on the paperless test through ¡TEST platform, this study summarizes the preparations and test procedures needed for conducting paperless computer-based English tests through ¡TEST platform. This study also finds that paperless computer-based English test through ¡TEST has a positive impact on students' English learning interests. It concludes that paperless computer-based English test through ¡TEST platform has high credibility and acceptability, which not only assists classroom English teaching, but also enhances their interests in learning English. © 2022 IEEE.

关键词： Teaching

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