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Methodological Comparison and Analysis for Six-Switching PMBLDC Motor Control 1

引用

12th international conference on Robotics Vision Signal Processing and Power applications

作者： Gujja, Musa Mohammed Ishak, Dahaman Hamidi, Muhammad Najwan Univ Sains Malaysia Sch Elect & Elect Engn Nibong Tebal Penang Malaysia

ISBN: (数字)9789819990054

ISBN: (纸本)9789819990078;9789819990054;9789819990047

Permanent Magnet Brushless Direct Current (PMBLDC) motor plays a significant role in our daily activities and its area of application is enormous. It can be seen in the areas of robotics, military, aerospace, domestic, and industrial machine among others. Hence, a precise approach to PMBLDC motor control is imperative. this study compares and evaluate three control strategy employing machine learning (ML), Response Optimizer (RO), and PID controller to attain the most suitable and effective PMBLDC motor control. A six-switching driver circuit was designed to drive the motor. the simulated result was analyzed both graphically and analytically. Some differences were observed in terms of overshoot, undershoot, rise, and settling time, however, all three-control approaches RO, ML, and PID follow the reference tracking.

关键词： machine learning Optimization PID Driver circuit PMBLDC motor

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Research on the application of Intelligent Technology in Electrical Automatic Control Engineering 4

Research on the Application of Intelligent Technology in Ele...

引用

4th international conference for Emerging Technology, INCET 2023

作者： Zheng, Wang Baotou Vocational & Technical College Baotou City014030 China

ISBN: (纸本)9798350335750

the application research of intelligent technology in electrical automatic control engineering is a research field to study the development and application of intelligent technology in electrical automatic control engineering. It also focuses on the development and application of artificial intelligence (AI) in this field, which is an important part of modern power system automation. the main focus areas include: high-speed circuit design, fault detection and isolation, smart grid management, distributed energy resource management, energy storage system and renewable energy system. the main challenge for researchers is to develop new algorithms to solve complex problems faster than traditional methods;Improve existing solutions to make them more efficient;It includes the research of intelligent control, artificial intelligence and machine learning, fuzzy logic, neural network and evolutionary computation. the main goal of this research is to develop an intelligent system for controlling processes or equipment with high accuracy and efficiency. © 2023 IEEE.

关键词： Fuzzy logic

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Enhanced Zero shot learning using Deep Neural Network ResNet50 4

Enhanced Zero shot Learning using Deep Neural Network ResNet...

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4th international conference for Emerging Technology, INCET 2023

作者： Khanam, Ansari Shaista Sonar, Poonam. N. Rajiv Gandhi Institute of Technology EXTC Department Mumbai India

ISBN: (纸本)9798350335750

computer vision has advanced with lot of development in visual recognition systems, which poses restrictions to expand for huge numbers of image classes. this restriction is due to huge image classes with unlabeled images which cannot be used in training the machine learning algorithm. As Traditional machine learning method of classification are based on the classification of categories which are available at the time of training. Technique of Zero-shot learning (ZSL) recognizes categories of test sets which is not appearing while training the model. the enhanced ZSL technique proposed is based on deep visual semantic embedding method. In this method Visual and semantic features are used for the classification of unknown categories. the extraction of visual features is accomplished with convolutional neural network (CNN) and ResNet 50. FastText is used to convert labels of classes into word embedding vectors. Visual and word embedding features are mapped. the model is predicting the Top 5 labels for an unknown image category (zero-shot class). the experiments are performed on standard datasets SUN and AWA2. the proposed technique of enhanced ZSL with ResNet 50 gives better accuracy and reduced model loss then CNN model. © 2023 IEEE.

关键词： Embeddings

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Detecting Distracted Drivers using Transfer learning and Image Classification Models 4

Detecting Distracted Drivers using Transfer Learning and Ima...

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4th international conference on Artificial Intelligence and computer Engineering, ICAICE 2023

作者： Jin, Yigao Harbin Institute of Technology Shandong Province Weihai City264209 China

ISBN: (纸本)9798400708831

Distracted driving is one of the major causes of car accidents worldwide, with specific behaviors such as talking on the phone or texting while driving. In the future, as human-machine co-driving becomes mainstream, monitoring drivers becomes crucial. this involves switching between different driving modes and taking measures when drivers are distracted. Deep learning techniques can effectively accomplish this task. this study focuses on the transfer learning of four image classification models and their application in detecting distracted drivers. these models can predict with varying degrees of accuracy whether a given image displays a distracted driver while driving. the models used in this study are Resnet, Nasnet, Dense, and VGG_with_MobileNet. Multiple optimized models were trained using different adjustment methods, and they all achieved an accuracy of over 93% on the AUC dataset. © 2023 ACM.

关键词： Image classification

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An Effective Method for Forecasting Crime Analysis using Deep learning Classifiers 4

An Effective Method for Forecasting Crime Analysis using Dee...

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4th IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Muthumanickam, K. Selvalakshmi, B. Vijayalakshmi, P. Nareshkumar, P. Department of Information Technology Tamilnadu Thottiyam India Tagore Engineering College Department of Computer and Engineering Tamilnadu Chennai India Department of Computer Science and Engineering Tamilnadu Salem India

ISBN: (纸本)9798350306118

Crime is one of our society's most serious issues. As a result of its pervasiveness in our culture and society, the task of preventing crime is one of the utmost crucial ones. the suggested model in this article is created to identify crime trends, and the aim of this research is to assess the efficacy of criminal inquiries based on inferences. the study draws conclusions from the crime scene and uses those conclusions to predict the offender. Here, the data set includes It includes details on the crime, such as the location's description, the type of crime, the date, the time, the latitude, and the longitude. Before training the model, data pre-processing will be performed, followed by feature selection and scaling to ensure high accuracy. the categorization techniques help the inquiry reach its objective, and this tactic helps identify a connection between two mathematical values. this technique forecasts the values of the dependent variables based on the independent variables, allowing the multilayer perceptron and machine learning reliant algorithm to classify the datasets and anticipate crimes with a higher degree of accuracy. the proposed method has obtained accuracy rates of 99.2%, recall rates of 98.91 %, precision rates of 98.08%, and F1-score rates of 96.44% in crime detection utilizing MLP architecture. © 2023 IEEE.

关键词： Crime

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Adapting Crop Recommendations to Local Climate Variability through machine learning 4

Adapting Crop Recommendations to Local Climate Variability T...

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4th IEEE international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： thirumala Akash, K. Mohammed Usman, F. Nitesh Kumar, T. Ahmed, Mohammed Riyaz Dxc Technology Analyst I Infrastructure Services Bengaluru India Reva University School Of Computing And Information Technology Bengaluru India Reva University School Of Multidisciplinary Studies Bengaluru India Hkbk College Of Engineering Department Of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350384628

Crop plantation has undergone significant transformations fueled by technological advancements and scientific knowledge, resulting in improved crop yields and quality. Traditionally reliant on manual labor and basic tools, such as plows, hoes, and sickles, farmers employed crop rotation and organic fertilization methods to enhance soil fertility. However, modern crop cultivation has embraced mechanization such as employing tractors, combines heavy machinery for planting, cultivation, and harvesting operations. Furthermore, precision agriculture techniques have been developed to optimize resource utilization and maximize crop production, including precision planting, irrigation, and fertilization. this research focuses on developing a machine-learning model for tailoring crop recommendations to local climate variability. By analyzing recorded weather data and crop yields, the model generates customized crop recommendations based on specific locations and conditions. Experimental results demonstrate the model's capability to incorporate weather patterns and accurately predict crop performance, leading to enhanced yields and sustainable agricultural practices. Future enhancements to the model could encompass additional factors like soil conditions and market demand, further refining the crop recommendation system. © 2023 IEEE.

关键词： machine learning

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Hybrid Deep learning Model for the SmartManufacturing 4

Hybrid Deep Learning Model for the SmartManufacturing

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4th IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2023

作者： Saini, Himani Sandhu, Jasminder Kaur Chandigarh University Department of Computer Science and Technology Punjab Mohali India

ISBN: (纸本)9798350306118

the efficacy as well as the standards of innovative manufacturing processes can be greatly enhanced by using deep learning models. Creating a hybrid artificial intelligence strategy for recognizing faulty casting products in intelligent manufacturing is the goal of this project. the recommended model uses pre-processed photo attributes to classify defective goods using the swin transform neural network. the objective is to enhance the quality inspection process in smart manufacturing by precisely recognizing and classifying casting faults. Using a matrix of ambiguity, the usefulness of the suggested technique is assessed, demonstrating both its ability to locate damaged products and its potential to improve both production quality and efficiency. © 2023 IEEE.

关键词： Long short-term memory

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Creative Product Design of Ceramic Technology Culture Integrated with machine learning 6

Creative Product Design of Ceramic Technology Culture Integr...

引用

6th international conference on computer Information Science and application Technology, CISAT 2023

作者： Lin, Tianyu Jinwon, Jeong Kookmin University Ceramics Department Major in Ceramic Crafts Korea Republic of

ISBN: (纸本)9781510668546

the development of ceramic technology cannot be separated from traditional culture. China is a country with a long history and has left many excellent works in various dynasties. the development of ceramic technology has attracted more and more attention. Ceramic process product design needs more innovative ideas to meet market demand. therefore, in this paper, machine learning technology is used to carry out data statistics and creative recommendations on product design, improve the design sense of ceramic technology and meet the needs of the masses. Qualitative and quantitative analysis and experimental methods are mainly used in this paper, with the help of machine learning, the related research on the creative design of ceramic craft culture. the experimental data show that in the field of ceramics, the training accuracy and test accuracy of the SVM model are kept above 80%, among which the weighted SVM algorithm has a higher grasp of the product accuracy. © 2023 SPIE.

关键词： machine learning

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application Study of Collaborative Multi-Model in Wordle Game 5

Application Study of Collaborative Multi-Model in Wordle Gam...

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5th international conference on machine learning and computer application, ICMLCA 2024

作者： Liu, Yan Tan, Jianyi Yang, Zicong Jin, Aitong Zheng, Yue Wang, Xinke School of Computer Science Zhuhai College of Science and Technology Zhuhai China School of Business Guangdong Ocean University Yangjiang China Media College Nanchang Institute of Technology Nanchang China

ISBN: (纸本)9798331530334

this study examines Wordle, a daily word puzzle game from the New York Times, focusing on its features and player behavior through an analysis of its crossword dataset. A neural network model was developed to predict outcome distributions for future dates, estimating the percentages of potential guesses (1, 2, 3, 4, 5, 6, X) using a sigmoid activation function and letter frequency-based weights. the model's effectiveness was validated by comparing average absolute percentage error (MAPE) values across MLPClassifier, RandomForestRegressor, and XGBRegressor, while addressing inherent uncertainties from limited datasets. Additionally, solution words were categorized by difficulty, with a specific assessment of the word 'ERNIE,' enhancing our understanding of the factors influencing word difficulty and guiding future guessing strategies to optimize player performance. © 2024 IEEE.

关键词： Neural network models

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New Deep learning Models for Medical Imaging: Deep Belief Network, GAN, Autoencoder 4

New Deep Learning Models for Medical Imaging: Deep Belief Ne...

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4th international conference on Smart Electronics and Communication, ICOSEC 2023

作者： Gupta, Richa Kumar Shukla, Surendra Tripathi, Vikas Graphic Era Deemed to Be University Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350300888

Deep learning (DL) is being utilized in different clinical imaging process and has accomplished promising results. Nonetheless, incorporating DL in clinical imaging also presents significant challenges. this research study presents the characteristics of clinical imaging that features both clinical requirements and specialized challenges and depicts how the patterns in DL are resolving these issues. this study presents a few contextual investigations that are commonly found, including advanced pathology and respiratory, chest, brain, and ophthalmology imaging. Rather than presenting a thorough writing review, this study highlights some notable exploration aspects associated with the contextual analysis. this study is concluded with a discussion and stating some possible future research directions. © 2023 IEEE.

关键词： Generative adversarial networks

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