检索结果-内蒙古大学图书馆

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Sankar, M. Chithambaramani, r. Sivaprakash, P. Ithayan, Vimala Charaan, r.M. dilip Marichamy, d. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331504403

This Paper presents an analysis of landlord land price prediction utilizing machine learning techniques. The objective is to develop a predictive model that can accurately forecast land prices, aiding landlords in making informed decisions regarding property investments. The research employs various machine learning algorithms, including but not limited to regression and ensemble methods, to analyze a dataset comprising relevant features such as location, land size, demographics, and economic indicators. The accuracy of the predictive models is evaluated through rigorous testing and validation processes, with performance metrics such as Mean Absolute Error (MAE), root Mean Square Error (rMSE), and r-squared (r2) utilized to gauge predictive accuracy, the accuracy of the deployed model is 94 percent. The findings demonstrate the efficacy of machine learning in predicting landlord land prices, with the proposed models achieving a high level of accuracy, thus offering valuable insights for landlords and real estate stakeholders in strategic decision-making processes. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Navigating Space: A ddPG-Based Approach to Autonomous Satellite Navigation 10

Navigating Space: A DDPG-Based Approach to Autonomous Satell...

引用

10th International Conference on Electrical Energy Systems, ICEES 2024

作者： Alex david, S. Appala, Charan Balurgi, Shreya Nagisetty, Anil Kumar Manam, Anusha Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350353778

This study developed a modern autonomous navigation system using proximity and accelerometer sensors, along with deep reinforcement learning algorithms. The system ensures safety by providing real-time data on obstacles and distance through proximity sensors, forming the basis for quick decision-making. Accelerometers measure movement precision and navigation orientation, determining the necessary distance and force for maneuvers. deep reinforcement learning, using ddPG algorithms, enables the system to learn and make decisions independently. The system can navigate, avoid obstacles, and seek cover autonomously, promoting the development of more independent systems. © 2024 IEEE.

关键词： Accelerometers

来源：评论

学校读者我要写书评

暂无评论

Enhancing Early diabetes detection using Ensemble Machine Learning Models for Improved Prediction and Patient Care 5

Enhancing Early Diabetes Detection using Ensemble Machine Le...

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Shanthini Watson Benjamin, Minu Inba Syed, Arshad Vamsi, Tamma raja Kumar, P.S.d.Sai Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Computer Science & Engineering Chennai India

ISBN: (纸本)9798331530013

Millions of individuals worldwide suffer from diabetes, a chronic condition that must be detected early to avoid major health issues like kidney failure, nerve damage, and heart disease. By using ensemble technique which combines machine learning (ML) approaches and evaluate the outputs and generates final prediction, then diabetes can be predicted more precisely. random Forest, Support Vector Machine (SVM), and Logistic regression, were the machine learning techniques and Voting Classifier is the ensemble classification model which were examined in this study. The study evaluated these model's ability to predict diabetes using datasets such as the Pima Indian diabetes dataset. Through the integration of Support Vector Machine (SVM), random Forest, and Logistic regression algorithms using a Voting Classifier, proposed model achieves an accuracy of 79%. This ensemble approach demonstrates superior performance compared to individual algorithms, with improved precision (0.81) and recall (0.78). It is identified that Predictive accuracy is found to be highly dependent on key parameters including glucose, BMI, and age with correlation coefficients of 0.47, 0.29, and 0.24 respectively. This method showed that combining multiple ML algorithms can significantly enhance diabetes diagnosis and care in addition to improving prediction capabilities. In the end, the study emphasizes how machine learning can completely change the way diabetes is treated and stresses how crucial it is to keep developing and using these technologies in order to improve patient outcomes. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization using grey relational analysis for wire EdM of aluminium matrix composites

引用

Materials Today: Proceedings 2023年 72卷 2395-2401页

作者： Udaya Prakash, J. Sivaprakasam, P. Jebarose Juliyana, S. Ananth, S. Sarala rubi, C. divya Sadhana, A. Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Mechanical Engineering College of Electrical and Mechanical Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia Department of Mechanical Engineering Vardhaman College of Engineering Shamshabad Telangana Hyderabad India Department of Physics Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

The creation of novel materials with high mechanical qualities necessitates the use of advanced machining techniques. Non-conventional machining processes alter the entire manufacturing scenario. Non-conventional machining processes swiftly replace conventional machining processes for obtaining better surface quality and a higher material removal rate. Based on grey relational analysis, this work proposes an efficacious method for optimising wire EdM machining parameters of AMCs with varied performance characteristics. Stir casting was used to make AMCs (413/B4Cp) using B4C of 3%, 6% and 9% by weight as reinforcement and 413 as the matrix material. In this study, performance features Mrr and Sr are taken into account while optimising input parameters. The experimented GrG is 0.772, while the anticipated value is 0.784. This method helped to improve the WEdM process. © 2022

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Ensemble of deep Learning Enabled Tamil Handwritten Character recognition Model 2nd

Ensemble of Deep Learning Enabled Tamil Handwritten Characte...

引用

2nd International Conference on Big data, Machine Learning, and Applications, BigdML 2021

作者： Thanga Selvi, r. Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9789819934805

recently, digitalization of handwritten characters has become a hot research topic and finds applicability in different domains. At the same time, recognition of Tamil handwritten characters is a tedious task compared to other languages. Therefore, this paper presents a new ensemble deep learning-based Tamil handwritten character recognition (EdL-THCr) model. The EdL-THCr model recognizes and classifies the Tamil handwritten characters. In addition, data preprocessing approach is involved using bilinear interpolation technique to normalize the images. Besides, an ensemble of capsule network (CapsNet) and VGGNet models take place for feature extraction process. Finally, softmax layer is employed to classify the Tamil characters in an effective way. A comprehensive experimental analysis is carried out on benchmark dataset, and the results portrayed the better performance of the EdL-THCr technique. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

A Novel Parasitic Mushroom-Like Structure with High Gain Microstrip Patch Antenna for Broadband Applications

A Novel Parasitic Mushroom-Like Structure with High Gain Mic...

引用

International Conference on Machine Learning and Big data Analytics, ICMLBdA 2023

作者： Sahaya Sheela, M. Syam Sudheer Babu, G. Sai durga Prasad, S.N.V. Vasanth Kumar, M.d. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of science and Technology Chennai India

ISBN: (纸本)9783031513374

In this research, a design for a microstrip patch antenna loaded with a parasitic mushroom-like structure is proposed. Antenna components include a rectangular microstrip patch as the main radiating element and one or more metallic patches as parasitic elements, separated by a dielectric layer. The parasitic patches are arranged in a pattern that resembles a mushroom growth, and their dimensions are optimized to improve the antenna’s performance. According to simulation results, the suggested antenna has a bandwidth of up to 20% and a high gain of up to 10dBi, which is much broader than that of a typical microstrip patch antenna. The radiation characteristics of the antenna are also improved, with a more uniform radiation pattern and higher front-to-back ratio. The suggested antenna design is appropriate for a variety of uses, including wireless communications, radar systems, and satellite communications, which call for high gain and broad coverage. The simplicity and low profile of the antenna make it easy to manufacture and integrate into various systems. Overall, the proposed parasitic mushroom-shaped microstrip patch antenna, which has broadband and high gain, is a promising solution for achieving improved antenna performance without increasing the antenna’s size or complexity. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Slot antennas

来源：评论

学校读者我要写书评

暂无评论

5G ready: A Compact Two-Port Antenna for Sub-6GHz Applications

5G Ready: A Compact Two-Port Antenna for Sub-6GHz Applicatio...

引用

2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Murugan, C. Kavitha, T. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

The new design is proposed based on Two-port antenna and Simulation outcome with an operating frequency range of 3.3-5.,5GHz, which covers N77, N78, N79 and Wireless Local Area Network (WLAN) bands. The newly coined antenna design achieves gain of 3dB and ensure trustworthy and effective communication in 5th Generation networks. Multiple Input and Multiple output (MIMO) parameters like Envelope Correlation Coefficient (ECC), Total Active reflection Coefficient (TArC)., diversity gain, Channel Capacity Loss (CCL) and radiation Efficiency which are measured in a multi-antenna system. The proposed antenna design illustrates excellent MIMO performance which achieves 5G Privileges likeenhanced mobile broadband (eMBB), ultra-reliable low-latency communications (UrLLC), and massive machine-type communications (mMTC). The Compact Size and Antenna radiation which makes it fit into 5G devices, like smartphones, tablets, and laptops. © 2025 IEEE.

关键词： Wireless local area networks (WLAN)

来源：评论

学校读者我要写书评

暂无评论

Improving Energy Efficiency in Wireless Sensor Network with Intelligent Energy Prediction Using Machine Learning Approach

Improving Energy Efficiency in Wireless Sensor Network with ...

引用

2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Panneerselvam, Bhuvaneswari devarasu, Neelamegam Pasupulati, Baburao Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350381887

In our day-to-day life, one of the emerging roles of green energy in wireless sensor network shoves the investigations of recent technological and economical solutions for solar energy. Saving external energy is one of the fundamental factors in any wireless sensor network with limited storage capacity. due to different environmental conditions, the energy conversation is too fast in the solar system and unconstrained atmospheric resource energy leads to operate the rechargeable batteries in the outdoor systems. However, some fluctuations occur in the environmental side. It is very crucial to predict the unnecessary errors in the sensing devices. Also, to examine the future energy and to maintain the system reliability in the solar powered wireless sensor network, the accurate prediction models are required. In this work, the Energy Efficient Nonlinear Autoregressive (EENA) algorithm using Machine Learning approach is proposed. With this approach, the algorithm effectively predicts the future energy status with respect to different time slots. The proposed algorithm gives a promising solution to prolong a battery life and the accurate predictions in the outdoor energy harvesting network. © 2024 IEEE.

关键词： Energy Harvesting Error Prediction Machine Learning Sensor network Solar

来源：评论

学校读者我要写书评

暂无评论

Federated Learning Approaches for decentralized data Processing in Edge Computing 5

Federated Learning Approaches for Decentralized Data Process...

引用

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Janaki, G. Umanandhini, d. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Computer Science & Engineering Chennai India

ISBN: (纸本)9798331504403

Federated Learning (FL) has evolved into a decentralized Machine Learning (ML) paradigm with a high potential for enabling model training across various Edge devices (Ed) to conserve data privacy. This survey explores the challenges and future directions of implementing FL in edge computing environments. This Comprehensive review addresses key technical challenges, including the heterogeneity of edge devices, resource constraints, security and privacy concerns, and communication overhead. To guide future research, this study highlights several promising research directions, including advanced model aggregation techniques, edge device optimization, cross-domain federated learning applications, robust security and privacy frameworks, and regulatory compliance. Additionally, This study reviews various Federated Learning methods-such as Federated Averaging (FedAvg), Federated Learning with Secure Aggregation (FedSecAgg), Hierarchical Federated Learning, and Peer-to-Peer Federated Learning-discussing their strengths, weaknesses, and suitable use cases. Finally, this review paper presents benchmarking results using standard datasets and performance metrics, comparing these approaches' efficiency, accuracy, scalability, and privacy preservation. This systematic review renders a broad perspective on the current trends and developments in federated Learning for edge computing, this analysis enlightenments researchers and Professionals with practical experience. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Feature Selection Technique–Based Approach for Author Profiling Using Word Embedding Techniques 8th

A Feature Selection Technique–Based Approach for Author Pro...

引用

8th International Conference on Computers, Management and Mathematical sciences, ICCM 2022

作者： Kavuri, Karunakar Kavitha, M. CSE Department Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9783031511660

Textual data are tremendously increasing on the World Wide Web through different social networking platforms, such as blogs, review sites, Facebook, Instagram, Twitter, etc. Crimes or frauds are also growing with the development of text in these platforms. Most of the users on these platforms create accounts with false information and send harassing and threatening messages. Knowing the details or basic information of text posted on these platforms is a very important task to control fraud. Author profiling (AP) is one technique used by the research community and social network administrators to know the author’s information related to messages posted on social networking platforms. Author profiling is a method of detecting demographic profiles such as age, gender, education, etc., of authors based on their written texts. Author profiling techniques are used in various applications of text processing, such as marketing, forensic analysis, and security-related fields. Most author profiling techniques use the content information of text to differentiate the writing styles of authors. The dataset contains a huge number of content words and, the identification of relevant words for differentiating the writing style of different authors is one challenging task to the research community. Feature selection algorithms are proposed by the researchers to find relevant features in the dataset. In this article, we developed a feature selection technique–based approach by using word embedding techniques for predicting the gender and age from the selected dataset. The PAN competition author profiling datasets are considered in this article for experimentation. In the proposed approach, word embedding techniques are used for converting words into word vectors. The similarity measure is used for finding the similarity among the word vectors. Similar words are grouped into clusters. Select the most important words from these clusters and consider them for experimentation. Selected w

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：