检索结果-内蒙古大学图书馆

Enhanced MADM Strategy with Heptapartitioned Neutrosophic Distance Metrics

Neutrosophic Sets and Systems 2025年 78卷 74-96页

作者： Eassa, Mohamed Myvizhi, M. Elkholy, Mohamed Abdelhafeez, Ahmed Elbehiery, Hussam Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Mathematics KPR Institute of Engineering and Technology Tamilnadu Coimbatore India Faculty of Computer Science& Engineering Alamein International University Egypt

In this work, a novel methodological approach to multi-attribute decision-making problems is developed and the notion of Heptapartitioned Neutrosophic Set Distance Measures (HNSDM) is introduced. By averaging the Penta-Partitioned Neutrosophic Distance Measures under particular conditional criteria, the suggested technique ranks the options. Additionally, we explore the fundamental characteristics of HNSDM and provide several illustrative theorems. The Heptapartitioned Neutrosophic Set Distance Measures are formulated based on the Hepta Neutrosophic Set. Lastly, a practical numerical example is provided to illustrate the efficacy of the suggested methodology. © 2025, University of New Mexico. All rights reserved.

关键词： Heptapartitioned Neutrosophic set Heptapartitioned Neutrosophic set and MADM strategy Heptapartitioned set Neutrosophic sine distance measure

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning based Plant Leaf Disease Detection Systems 14

Comparative Analysis of Machine Learning based Plant Leaf Di...

引用

14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Jamadar, Riyazahemed A. Sharma, Anoop Wagh, Kishor Department of Computer Science& Engineering Singhania University Rajasthan India Department of Computer Engineering AISSMS IOIT Pune India

Recently the availability of Machine Learning(ML) algorithms through state of the art programming interfaces & tools has lead the research community to employ ML based object detection/classification algorithms & techniques for the research work with improved accuracy & performance. There is a significant amount of research work that employs ML based approaches for plant leaf disease detection & classification. A systematic study and comparative analysis of these ML algorithms provide a good insight to researchers and guide them to select & blend these ML algorithms for higher accuracy and performance. In this paper an effort is made to establish comparative analysis of the most recent work done in this domain, The ML algorithms have been analyzed against parameters like the data set, preprocessing techniques, feature extraction methods and accuracy, and the type of diseases that could be detected. Every analysis concisely discusses the characteristics and scope for further extensions of the proposed technique/method. © Grenze Scientific Society, 2023.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Load Balancing in Cloud Computing: Techniques, Challenges and Future Prospects 1

Load Balancing in Cloud Computing: Techniques, Challenges an...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Agarwal, Srishti Singh, Jitendra Ansari, M.I.H. SRM Institute of Science& Technology Department of Computer Science& Engineering U.P. Ghaziabad201204 India SRM Institute of Science & Technology Delhi NCR Campus CSE department Modinagar U.P. Ghaziabad201204 India Meerut Institute of Technology Department of Computer Science & Engineering U.P. Meerut India

ISBN: (纸本)9798350353648

Load balancing is a critical aspect of optimizing resource utilization and performance in cloud computing environments. This paper begins by introducing the fundamental concepts of load balancing and underscoring its significance in achieving scalability, efficiency, and user satisfaction within cloud ecosystems & presents a comprehensive exploration of load balancing techniques in cloud environment. The objectives of the paper are to unveil a spectrum of load balancing techniques, discuss challenges inherent to load distribution, and identify potential future prospects for this evolving field. A comparative analysis of the various approaches highlights their respective strengths and weaknesses, considering parameters like performance, scalability, and implementation complexity. With an extensive survey of the literature, this paper provides researchers and practitioners with a holistic perspective on load balancing in cloud computing. © 2024 IEEE.

关键词： Cloud Computing Future Prospects Load Balancing Resource Optimization Scalability

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Contingency-Based Learning Strategies for Precision Medicine 15

Evaluation of Contingency-Based Learning Strategies for Prec...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Kaushik, Harshita Rajendran, Naveen Kumar Kumar, Ashwini Vivekananda Global University Department of Computer Science& Application Jaipur India Department of Aerospace Engineering Karnataka Bangalore India Arka Jain University Department of Mechnical Engineering Jharkhand Jamshedpur India

ISBN: (纸本)9798350370249

Contingency-based learning strategies primarily based on synthetic intelligence (AI) are being hired within the area of precision remedy to enable greater powerful selection-making when treating patients. The overall performance of such learning strategies should be evaluated to make sure they are presenting accurate and dependable outcomes. This paper aims to assess contingency-based learning strategies for precision medication to help clinicians and researchers appropriately assess the efficacy of these learning techniques and decide the first-rate method for given software., a scientific evaluation of the current literature was undertaken to identify existing assessment strategies and analyze their strengths and weaknesses. The assessment criteria used in this analysis are accuracy, interpretability, complexity, scalability, and transferability, which had been selected as they affect the performance of AI-primarily based approaches in real-international settings. Furthermore, a discussion of current equipment and frameworks that could be used to assess AI-based techniques in the area of precision remedy was performed. From this assessment, it has been discovered that most of the present assessment techniques lack the necessary accuracy and transferability essential to appropriately check the efficacy of AI-based strategies for precision medicinal drugs. But, sure, evaluation metrics, together with explain ability, may be employed to degree the overall performance of AI-primarily based techniques in order to decide the nice approach for a given application. © 2024 IEEE.

关键词： Contingency Intelligence Interpretability Scalability Software Strategies

来源：评论

学校读者我要写书评

暂无评论

Mining of Frequent and High Utility Fuzzy Sequential Patterns 1

Mining of Frequent and High Utility Fuzzy Sequential Pattern...

引用

1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Ritika Gupta, Sunil Kumar I K Gujral Punjab Technical University Department of Computer Science& Engineering India Sardar Beant Singh State University Department of Computer Science& Engineering India

ISBN: (纸本)9781665497107

Sequential pattern mining is one of the very popular data mining techniques to find patterns from databases. The variation in technique is based on the threshold used for mining which can be frequency, utility, or both. The use of fuzzy theory helps to provide natural representation by expressing parameters in linguistic terms. This paper proposes a hybrid fuzzy sequential pattern mining algorithm that expresses quantity in linguistic terms. The proposed method generates less number of patterns than the existing algorithms, according to the results of the experiments. © 2022 IEEE.

关键词： Linguistics

来源：评论

学校读者我要写书评

暂无评论

Optimization Technique to Reduce Resource Utilization of Software Key Loggers Using PSO 3

Optimization Technique to Reduce Resource Utilization of Sof...

引用

3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Sharma, Yashika Rana, Muskaan Apex Institute of Technology Chandigarh University Mohali India Chandigarh University Department of Computer Science& Engineering Mohali India

ISBN: (纸本)9798350322842

Software key loggers are the leading type of keylogging. Both cheap and consumer-specific and specially created keylogging programs are easily accessible online. These key loggers should be revised to each target operating system to guarantee the appropriate handing of I/O devices. Therefore, system differences inevitably initiate operating system-based devices of software key loggers: keyboard state tables, system routine hooks, and the adoption of kernel-mode layered drivers. It is analyzed that software key logger has high execution time and resource utilization. In this research work, the PSO technique is applied which will optimize the software key loggers. The proposed model is implemented in MATLAB and results are analyzed in terms of execution time, resource utilization. © 2023 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Enhancement of Level of Security using Wireshark Through Continuous Monitoring and Detection System 4

Enhancement of Level of Security using Wireshark Through Con...

引用

4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Bhat, C.Rohith Mane, Sulakshana Bhausaheb Bhatt, Chandradeep Verma, Garima Naser, Sarmad Jaafar Jweeg, Muhsin Department of Computer Science and Engineering India Bharati Vidyapeeth College of Engineering Department of Computer Engineering Navi Mumbai India Graphic Era Hill University Computer Science and Engineering Dehardun248002 India Graphic Era Deemed to Be University Computer Science& Engineering Uttarakhand Dehradun248002 India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350360165

We suggest using edge computing to install an intrusion detection system (IDS) at the network edge in order to address the problem of intrusion detection in wireless sensor networks (WSNs). This IDS functions as a proactive defence system designed specifically with WSNs in mind. Our method combines an arithmetic optimisation algorithm (AOA) with Wireshark and machine learning to create an edge intelligence framework for identifying denial-of-service (DoS) assaults in wireless sensor networks (WSNs). We use the wireshark for optimisation adjustment and a parallel strategy to promote communication between populations in order to increase model accuracy. Our model achieves 98.9% accuracy (ACC) through simulated studies utilising the IDS dataset in Matlab2018b. The effectiveness and practical significance of our suggested intrusion detection approach are highlighted by these experimental results. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Study of Case-Based Reasoning in Information Retrieval: An Artificial Intelligence Approach

A Comprehensive Study of Case-Based Reasoning in Information...

引用

2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Solanki, Surabhi Verma, Seema Biswas, Prolay Roy, Pulakesh Singh, Aparna Sharma, Surbhi Computer Science & Engineering Banasthali Vidyapith Rajasthan Tonk India Scset Bennett University Greater Noida India Education National Institute of Technical Teachers' Training and Research Department of Electrical & Electronics Engineering Bhopal India Computer Science & Engineering Dayananda Sagar University Ramanagara India Computer Science& Engg Brainware University Kolkata India

ISBN: (纸本)9798331508685

Information Retrieval (IR) systems which provide accurate and contextually relevant information to healthcare and law etc. where accuracy is very crucial. Traditional information retrieval methods fundamentally based on keyword matching and statistical models usually difficult to achieve the semantic meaning and contextual nuances of queries. Case-Based Reasoning (CBR), as an artificial intelligence technique, provide advance solutions to enhance IR systems based on a set of past cases through adaptive context-supporting retrieval. By taking advantage of past cases data, CBR allows IR systems to interpret complex context-sensitive queries and offer personalized results. The paper provides an overview of traditional IR models, examines the CBR integration into these systems, and evaluates the impact of CBR on retrieval effectiveness and personalization. And finally, we elaborate on the challenges involved with scaling and adapting cases towards real-time retrieval and provide some future directions for research, including integrating machine learning techniques and hybrid models to enhance the relevance, interpretability, and scalability of CBR-based IR systems. © 2025 IEEE.

关键词： Case based reasoning

来源：评论

学校读者我要写书评

暂无评论

Utilizing a Machine Learning Approach, Chronic Disease Identification and Prediction

Utilizing a Machine Learning Approach, Chronic Disease Ident...

引用

Communication, computer sciences and engineering (IC3SE), International Conference on

作者： Vandna Bansla Rita K Saini Department of Computer Science& Engineering Himalayiya University Dehradun Uttarakhand India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Nowadays, people suffer from many diseases due to lifestyle choices and environment. Recognition and predicting these diseases in their early stages is crucial to preventing their extremes. Mostly time, identifying diseases manually poses a significant challenge for doctors. The purpose of this study to determine and forecast the patients who have greater prevalent long-term conditions. This might be accomplished by ensuring that this classification accurately identifies people with chronic illnesses by applying a machine learning technique. The disease prediction is also difficult a difficult challenge. Therefore, data mining is essential to the prediction of disease. The system provides a wide range of features depend on the patient's diagnostic by using machine learning algorithms like convolutional neural networks (CNN) for impulsive attribute extraction and disorder prediction and Knearest neighbour (KNN) for calculating distances to discover the accurate match in the dataset and the concluding disorder prediction. Prognosis of the disorder. The process of creating the data set included obtaining details on the patient's lifestyle, medical consultation history, and the symptoms of the illness. All of these factors were taken into account while making this general illness prediction. To sum up, this study compares the recommended system utilizing a variety of methods, such as logistic regression, decision trees, and Naïve Bayes.

关键词： Logistic regression Accuracy Machine learning Nearest neighbor methods Feature extraction Bayes methods Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of an AI-enabled State-of-the-Art Models for the Detection of DDoS Attacks on IoT Devices

Comparative Analysis of an AI-enabled State-of-the-Art Model...

引用

Disruptive Technologies (ICDT), International Conference on

作者： Rajneesh Kumar Gaurav Gulati Bhupesh Gupta Mohit Chhabra Department of Computer Science & Engineering Maharishi Markandeshwar Engineering College MMDU Mullana Haryana India Department of Computer Science& Engineering IMS Engineering College Ghaziabad UP India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

With technological advancement, Distributed Denial of Service (DDoS) attacks are gaining momentum in IoT networks. DDoS attacks are widely spreading on IoT devices since they have limited resources (memory) and no efficient security models. Different security measures are available to protect IoT devices from attacks. Some of these are firewalls, Intrusion detection systems, etc. Recently, researchers have utilized Artificial Intelligence for early detection of attacks due to its capability of detecting menaced attacks and, hence, boosting security. In this paper, a rigorous survey of different AI-enabled state-of-the-art models for detecting DDoS Attacks was done, and the future direction and scope of improvement for early Detection of DDoS attacks on IoT devices were highlighted.

关键词： Surveys Analytical models Firewalls (computing) Memory management Intrusion detection Denial-of-service attack Internet of Things Security Artificial intelligence Disruptive technologies

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：