检索结果-南通市图书馆

Metaheuristic Based Clustering with Deep Learning Model for Big Data Classification

Computer Systems Science & Engineering 2023年第1期44卷 391-406页

作者： R.Krishnaswamy kamalraj subramaniam V.Nandini K.Vijayalakshmi Seifedine Kadry Yunyoung Nam Department of Electronics and Communication Engineering University College of Engineering AriyalurAriyalur621704India Department of Biomedical Engineering Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatore641021India Department of Computer Science and Engineering Sona College of TechnologySalem636005India Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai600077India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,a massive quantity of data is being produced from a distinct number of sources and the size of the daily created on the Internet has crossed two *** the same time,clustering is one of the efficient techniques for mining big data to extract the useful and hidden patterns that exist in ***-based clustering techniques have gained significant attention owing to the fact that it helps to effectively recognize complex patterns in spatial *** data clustering is a trivial process owing to the increasing quantity of data which can be solved by the use of Map Reduce *** this motivation,this paper presents an efficient Map Reduce based hybrid density based clustering and classification algorithm for big data analytics(MR-HDBCC).The proposed MR-HDBCC technique is executed on Map Reduce tool for handling the big *** addition,the MR-HDBCC technique involves three distinct processes namely pre-processing,clustering,and *** proposed model utilizes the Density-Based Spatial Clustering of Applications with Noise(DBSCAN)techni-que which is capable of detecting random shapes and diverse clusters with noisy *** improving the performance of the DBSCAN technique,a hybrid model using cockroach swarm optimization(CSO)algorithm is developed for the exploration of the search space and determine the optimal parameters for density based ***,bidirectional gated recurrent neural network(BGRNN)is employed for the classification of big *** experimental validation of the proposed MR-HDBCC technique takes place using the benchmark dataset and the simulation outcomes demonstrate the promising performance of the proposed model interms of different measures.

关键词： Big data data classification clustering mapreduce dbscan algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Paddy Leaf Disease Detection Using an Optimized Deep Neural Network

引用

Computers, Materials & Continua 2021年第7期68卷 1117-1128页

作者： Shankaranarayanan Nalini Nagappan Krishnaraj Thangaiyan Jayasankar Kalimuthu Vinothkumar Antony Sagai Francis Britto kamalraj subramaniam Chokkaligam Bharatiraja Department of Computer Science&Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India School of Computing SRM Institute of Science and TechnologyKattankulathur603203India Department of Electronics and Communication Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India Department of Electronics&Communication Engineering SSM Institute of Engineering and TechnologyDindigul624002India Department of Mechanical Engineering Rohini College of Engineering and TechnologyPalkulam629401India Department of ECE Karpagam Academy of Higher EducationCoimbatore641021India Department of Electrical and Electronics Engineering SRM Institute of Science and TechnologyChennai603203India

Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the *** diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming *** of diseases from the plant images is an active research topic which makes use of machine learning(ML)approaches.A novel deep neural network(DNN)classification model is proposed for the identification of paddy leaf disease using plant image *** errors were minimized by optimizing weights and biases in the DNN model using a crow search algorithm(CSA)during both the standard pre-training and fine-tuning *** DNN-CSA architecture enables the use of simplistic statistical learning techniques with a decreased computational workload,ensuring high classification *** leaf images were first preprocessed,and the areas indicative of disease were initially extracted using a k-means clustering *** was then applied to eliminate regions not indicative of ***,a set of features were extracted from the previously isolated diseased ***,the classification accuracy and efficiency of the proposed DNN-CSA model were verified experimentally and shown to be superior to a support vector machine with multiple cross-fold validations.

关键词： Leaf classification paddy leaf deep learning metaheuristics optimization crow search algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

VLSI Implementation of Optimized 2D SIMM Chaotic Map for Image Encryption

引用

Intelligent Automation & Soft Computing 2023年第3期35卷 3155-3168页

作者： M.Sundar Prakash Balaji V.R.Vijaykumar kamalraj subramaniam M.Kannan V.Ayyem Pillai Department of Electronics and Communication Engineering RVS College of Engineering and TechnologyCoimbatore641402India Department of Electronics and Communication Engineering Anna University Regional CampusCoimbatore641046India Department of Biomedical Engineering Karpagam Academy of Higher EducationCoimbatore641021India Department of Electronics MIT CampusChennai600044India Department of Electronics and Communication Engineering Gokaraju Rangaraju Institute of Engineering and TechnologyHyderabad500090India

The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with inﬁnite collapse Mod-ulation Map)model for image *** proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Inﬁnite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM *** chaotic sequences,generated using 2D-SIMM model,are sensitive to initial *** the proposed algorithm,these initial conditions are optimized using JAYA optimization *** coefﬁcient and entropy are considered asﬁtness functions in this study to evaluate the best solution for initial *** simulation results clearly shows that the proposed algorithm achieved a better performance over existing *** addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system *** optimization,the correlation coefﬁcient was-0.014096 and without optimization,it was 0.002585.

关键词： Chaotic mapping 2D-SIMM encryption decryption jaya optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

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：