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检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 777 条记录，以下是71-80 订阅

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Research on Rolling Bearing Fault Diagnosis Based on Distributed Fuzzy Broad learning System Under Imbalanced Data 5

Research on Rolling Bearing Fault Diagnosis Based on Distrib...

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5th international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Pan, Haiyang Liu, Haoran Zheng, Jinde Tong, Jinyu Cheng, Jian School of Mechanical Engineering Anhui University of Technology Ma'anshan243032 China

ISBN: (纸本)9798331529192

As a novel fast and effective intelligent algorithm, Broad learning System (BLS) is popularly used in data classification task. However, the real data are often imbalanced, which makes BLS have limited performance in dealing with imbalanced data and cannot achieve good classification results. In view of this, a method based on Distributed Fuzzy Broad learning System (DFBLS) under imbalanced data is proposed in this paper. the model assigns a fuzzy affiliation value to each training point, reducing the effect of imbalanced samples on the model, and DFBLS executes fuzzy function in parallel, thus improving computational efficiency and processing speed. Moreover, DFBLS learns the features in the input data by mapping features and enhancement features, which solves the deficiency of fuzzification that leads to the loss or confusion of data samples. Finally, it is validated by two rolling bearing experimental datasets, and the research results show that this technology has demonstrated excellent performance in various evaluation indexes and provides an efficient solution to the fault diagnosis problem in imbalanced data sets. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhanced Extra Trees Classifier for Epileptic Seizure Prediction 5

Enhanced Extra Trees Classifier for Epileptic Seizure Predic...

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5th international conference on signal processing and Information Security, ICSPIS 2022

作者： Ntahobari, Maurice Kuhlmann, Levin Boley, Mario Hesabi, Zhinoos Razavi AI Monash University Dept. Data Science MelbourneVIC Australia Melbourne University Dept. Medicine MelbourneVIC Australia

ISBN: (纸本)9781665492652

For a machine learning based epileptic seizure prediction, it is important for the model to be implemented in small and implantable or wearable devices. these devices can be used to monitor the epileptic patients. However, the current state-of-the-art seizure prediction methods are complex and computationally intensive. We use SHapley Additive exPlanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p © 2022 IEEE.

关键词： machine learning

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From Titles to Genres: An Exploration of machine learning Techniques in Movie Classification 5th

From Titles to Genres: An Exploration of Machine Learning Te...

引用

5th international conference on 3D Imaging Technologies-Multidimensional signal processing and Deep learning, 3DIT-MSP and DL 2023

作者： Zhang, Zhaohuan College of Information Science and Technology/College of Cyber Security Jinan University Guangzhou China

ISBN: (纸本)9789819751839

the application of machine learning models to identify the genre of movies based on their titles and overviews is explored in this research paper. the "Movie Title" dataset from Kaggle is the source of the data for this investigation. the study examines the data, carries out the necessary cleaning and manipulation, creates a word cloud to visualize frequently occurring terms, resamples the data for a better distribution of genres, and employs two models for genre prediction: BERT (Bidirectional Encoder Representations from Transformers) and TF-IDF (Term Frequency-Inverse Document Frequency). the performance of both models is evaluated using accuracy and/or loss metrics, and conclusions are drawn based on the findings. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Distribution transformers

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CROP ANALYSIS AND PREDICTION 5

CROP ANALYSIS AND PREDICTION

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5th international conference on Multimedia, signal processing and Communication Technologies (IMPACT)

作者： Verma, Ruchi Jaypee Univ Informat Technol Waknaghat Dept Comp Sci & Engn & Informat Technol Solan India

ISBN: (纸本)9781665476478

For decades, agriculture has been the backbone of our country's economy, a way of survival for half of our country's population and therefore the farmers must produce good quality crops and livestock. Analysis of environmental and soil conditions, including moisture and ph level, temperature, and chemical composition plays a vital role in the well-being of a good quality product. Today, machine learning is well-equipped regarding analysis of such data, enabling crops to be grown at much higher precision, empowering farmers to be more confident about their decisions, and allowing them to treat their harvest with certainty and care. Like every other study regarding agriculture development with the sole goal of creating an accurate and efficient model for crop classification, the present research also deals with the systematic review of such yields, evaluating crop quality for individual plant species such as apples, chickpea, coconut, coffee, mango, rice, etc to detect crop disease and weed infestations taking extreme weather and soil conditions into account and providing a detailed analysis in terms of accuracy using five major machine learning models namely KNN, SVC, Random Forest, Decision Tree, and Gradient Boosting. In our result analysis, we have achieved an accuracy of 99.4% while analyzing which crop will produce the best yield in given weather and soil condition.

关键词： Crop Analysis machine learning Yield Prediction Hyper Parametrization Algorithm Soil condition

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Comparative Analysis of machine learning Approaches to Assess Stability in Micro Grid 5th

Comparative Analysis of Machine Learning Approaches to Asses...

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5th international conference on Cognitive Computing and Information processing, CCIP 2023

作者： Neethi, M. Sahana, B. Department of Electrical and Electronics Engineering JSS Science and Technology University Mysuru India

ISBN: (纸本)9783031607240

Traditionally, electricity generation was localized, with a single power plant supplying power to surrounding towns and using only fossil fuels, but as modernization began, increasing electricity demand meant many Blackouts, distribution imbalances, and unavailability of power supply all these issues have resulted in high energy costs also in terms of pollution. the idea of a microgrid is growing in popularity as a means of addressing environmental pollution and raising energy demands. the features of Micro grid differ significantly from those of the traditional grid because distributed energy sources (DERs) are typically interfaced with the utility grid by inverters. In this work algorithms like Deep learning, and LSTM, are compared with KNN a machine learning Algorithm and both are used to evaluate for transient, frequency, and small signal stability in an 18-bus test system while comparing. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Fossil fuels

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Human Finger Motion Analysis Based on machine learning 5

Human Finger Motion Analysis Based on Machine Learning

引用

5th international conference on machine learning and Natural Language processing (MLNLP)

作者： Wang Jiaming Univ Chinese Acad Sci Coll Artificial Intelligence Beijing Peoples R China

ISBN: (纸本)9781450399067

In modern medicine, doctors can use ultrasonic equipment to detect hand tendon slippage. However, due to the lack of obvious characteristics of the tendon on the ultrasound image, it is difficult to analyze the amount of tendon slippage when the hand is moving with eyes. In order to solve the shortage of medical image tracking, this paper proposes a real-time tracking algorithm based on target tracking by using control theory, image analysis and image processing technology. In this paper, ultrasonic equipment is used to collect the motion image data of the hand tendon, and the target tracking algorithm is used to realize the tracking of the hand tendon. three feature points of eight image sequences are tracked, and the tracking rate is 70%. However, some tracking frames disappear and cannot be tracked. through the image processing and improvement, the contrast is increased, the tracking effect is enhanced to a certain extent, the tracking rate remains above 75%, and the loss situation has been greatly improved.

关键词： TLD tracking tendon movement image analysis

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A Method of machine learning for Social Bot Detection Combined with Sentiment Analysis 5

A Method of Machine Learning for Social Bot Detection Combin...

引用

5th international conference on machine learning and Natural Language processing (MLNLP)

作者： Long, Guanghua Lin, Deyu Lei, Jie Guo, Zhiyong Hu, Yangyang Xia, Linglin Nanchang Univ Sch Software Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781450399067

Social Bot exists widely in major social networks. Some maliciously use a social bot to guide public opinion, steal user privacy, and create rumors, which seriously affects the security of social networks. Past approaches mainly extracted large amounts of contents but ignored bots' text sentiment features, and it is hard to detect social bot just based on contents. this paper proposes a malicious social bot detection method that combines sentiment features in response to this problem. It trains a Bidirectional Long Short-Term Memory model(Bi-LSTM) with an Attention Mechanism to perform sentiment calculation on the online text information of social accounts and analyze the sentiment fluctuations of accounts to get the new sentiment features;then, it inputs the new features combined with metadata features into different machine learning models for analysis and comparison. through this method, different machine learning detection models have improved the detection accuracy after combining sentiment features.

关键词： malicious social bot Bi-LSTM attention mechanism sentiment machine learning

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5th international conference on Advances in Distributed Computing and machine learning, ICADCML 2024

5th International Conference on Advances in Distributed Comp...

引用

5th international conference on Advances in Distributed Computing and machine learning, ICADCML 2024

ISBN: (纸本)9789819718405

the proceedings contain 35 papers. the special focus in this conference is on Advances in Distributed Computing and machine learning. the topics include: Computer-Aided Bundle Branch Block Detection Using Symbolic Features of ECG signal;block-Chain and Cloud-Based Tender Allocation System;reliability Assessment of IoT-Enabled Systems Using Fault Trees and Bayesian Networks;resnet-50 Integrated with Attention Mechanism for Remote Sensing Classification;revolutionizing Data Annotation with Convergence of Deep learning and Active learning to Enhance Credibility on Twitter Datasets;statistical and Deep-learning Approaches for Individual Carbon Footprint Calculation in India;intelligent Healthcare System Using Emerging Technologies: A Comprehensive Survey;Efficient Energy Management by Using SJF Scheduling in Wireless Sensor Network;cost Effective and Energy Efficient Drip Irrigation System for IoT Enabled Smart Agriculture;facial Detection and Recognition in Drone Imagery Using FaceNet;valluvan: processing Name Board Images to Enhance Communication for Native Tamil Speakers;Optimized VM Migration for Energy and Cost Reduction Using TSO Algorithm in Cloud Computing;A Study on the Mental Health Among Indian Population in the Post COVID-19 Pandemic Using Computational Intelligence;Cloud-Based Anomaly Detection for Broken Rail Track Using LSTM Autoencoders and Cross-modal Audio Analysis;Face Recognition Using CNN for Monitoring and Surveillance of Neurological Disorder Patients;a Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-colour Space Feature Fusion and Quantum–Classical Stack Ensemble Method;comparative Analysis of Deep learning-Based Hybrid Algorithms for Liver Disease Prediction;preface;performance Improvements of Covert Timing Channel Detection in the Era of Artificial Intelligence;sign Detection Using an N-Gram Language Model and MobileNet.

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5th international conference on Advances in Distributed Computing and machine learning, ICADCML 2024

5th International Conference on Advances in Distributed Comp...

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5th international conference on Advances in Distributed Computing and machine learning, ICADCML 2024

ISBN: (纸本)9789819735228

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Performance Comparison of Credit Card Fraud Detection System using machine learning 5

Performance Comparison of Credit Card Fraud Detection System...

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5th international conference on signal processing and Information Security, ICSPIS 2022

作者： Panthakkan, Alavikunhu Valappil, Najiya Appathil, Majida Verma, Seema Mansoor, Wathiq Al-Ahmad, Hussain University of Dubai Dubai United Arab Emirates Banasthali Vidyapith Rajasthan India

ISBN: (纸本)9781665492652

Cyber security is becoming an integral part of modern life, tackling abnormal activities being the main challenge in the domain. To find and abort a fishy transaction is the procedure for maintain the security in credit cards. With the availability of past datasets, machine learning algorithms have made it possible to detect abnormal activities among the transactions. the aim of the paper is to create a balanced data from a pre-existing dataset and to apply six different machine learning algorithms like Decision tree, K-Nearest Neighbor, Logistic regression, SVM, Random Forest and XGBoost to detect fraud activities. Later, the results are compared and discussed on the basis of evaluation matrices which include precision, recall, f1-score and accuracy. All the algorithms are applied on three sets of data, where the ratio of fraud to valid transactions is varied. three cases are considered with ratios as 1:100, 1:10 and 1:1. A balanced dataset showed greater performance in the terms of all evaluation matrices. © 2022 IEEE.

关键词： Decision trees

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