標題: Titlebook: Evolutionary Data Clustering: Algorithms and Applications; Ibrahim Aljarah,Hossam Faris,Seyedali Mirjalili Book 2021 The Editor(s) (if app [打印本頁] 作者: Colossal 時間: 2025-3-21 18:16
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書目名稱Evolutionary Data Clustering: Algorithms and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Evolutionary Data Clustering: Algorithms and Applications被引頻次
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書目名稱Evolutionary Data Clustering: Algorithms and Applications讀者反饋
書目名稱Evolutionary Data Clustering: Algorithms and Applications讀者反饋學(xué)科排名
作者: 上下倒置 時間: 2025-3-21 22:18 作者: Oration 時間: 2025-3-22 00:39
2524-7565 thms used to data clustering.Serves as a reference resource This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective ev作者: pulmonary-edema 時間: 2025-3-22 07:06 作者: 談判 時間: 2025-3-22 10:04
https://doi.org/10.1007/978-3-531-93197-5timization—GWO (APGWO) for the routing phase. Our approach gives results very close to the exact solutions and better than the original k-Means algorithm. And for the routing phase, our experimental results show highly competitive solutions compared with recent approaches using PSO and GWO on many of the benchmark datasets.作者: Default 時間: 2025-3-22 13:12
Evanescent Waves in Optical Waveguides,s a review on integrating several evolutionary algorithms with clustering techniques to perform image segmentation. We choose some of the most common applications on the topic, which are Medical, Multi-objective, and Multilevel Thresholding image segmentation techniques. Then, other applications in the field are also reviewed.作者: Default 時間: 2025-3-22 17:54 作者: Working-Memory 時間: 2025-3-22 21:17
,Capacitated Vehicle Routing Problem—A New Clustering Approach Based on Hybridization of Adaptive Patimization—GWO (APGWO) for the routing phase. Our approach gives results very close to the exact solutions and better than the original k-Means algorithm. And for the routing phase, our experimental results show highly competitive solutions compared with recent approaches using PSO and GWO on many of the benchmark datasets.作者: Abominate 時間: 2025-3-23 02:41
A Review of Evolutionary Data Clustering Algorithms for Image Segmentation,s a review on integrating several evolutionary algorithms with clustering techniques to perform image segmentation. We choose some of the most common applications on the topic, which are Medical, Multi-objective, and Multilevel Thresholding image segmentation techniques. Then, other applications in the field are also reviewed.作者: Credence 時間: 2025-3-23 07:21 作者: 野蠻 時間: 2025-3-23 09:56 作者: Aggressive 時間: 2025-3-23 15:46
Evaluation Research and Fundamental Researchrdingly, data clustering has an increasing interest in various applications involving health, humanities, and industry. Assessing the goodness of clustering has been widely debated across the history of clustering analysis, which led to the emergence of abundant clustering evaluation measures. The a作者: 織物 時間: 2025-3-23 19:24
https://doi.org/10.1007/978-3-642-82539-2ation algorithms is the Grey Wolf Optimizer (GWO). In this chapter, we use GWO on seven medical data sets to optimize the initial clustering centroids represented by the individuals of each population at each iteration. The aim is to minimize the distances between instances of the same cluster to pr作者: MIME 時間: 2025-3-24 01:48 作者: GROSS 時間: 2025-3-24 04:22
https://doi.org/10.1007/978-3-531-93197-5sts. However, no standard method has been established yet to obtain optimal solutions for all standard problems. In this research, we propose a two-phase approach: An improved k-Means algorithm for the clustering phase and a hybrid meta-heuristic based on Adaptive Particle Swarm—PSO and Grey Wolf Op作者: 有危險 時間: 2025-3-24 07:48 作者: 門窗的側(cè)柱 時間: 2025-3-24 12:29
Studienbücher zur Sozialwissenschaftblems. HHO algorithm processes a population of search space with two operations: Soft besiege and Hard besiege. One of main problems in the use of population-based algorithms is premature convergence. A premature stagnation of the search creates a shortage of diversity, which affects the relationshi作者: 捕鯨魚叉 時間: 2025-3-24 15:00
https://doi.org/10.1057/9780230615489milarity/dissimilarity between these instances. This process is called unsupervised learning. Detecting the data structure is not an easy task, especially if there are no previous assumptions to guide the clustering process. Multi-objective evolutionary algorithms have been used as alternative solut作者: 提升 時間: 2025-3-24 19:25 作者: 事與愿違 時間: 2025-3-25 01:38 作者: 生命層 時間: 2025-3-25 06:06 作者: allergy 時間: 2025-3-25 10:35 作者: JAUNT 時間: 2025-3-25 15:16 作者: upstart 時間: 2025-3-25 19:22
Algorithms for Intelligent Systemshttp://image.papertrans.cn/e/image/317917.jpg作者: 紀念 時間: 2025-3-25 23:19
978-981-33-4193-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: 內(nèi)行 時間: 2025-3-26 00:17
Evolutionary Data Clustering: Algorithms and Applications978-981-33-4191-3Series ISSN 2524-7565 Series E-ISSN 2524-7573 作者: jaunty 時間: 2025-3-26 07:48
Introduction to Evolutionary Data Clustering and Its Applications,, clustering has a crucial role in numerous types of applications. Essentially, the applications include social sciences, biological and medical applications, information retrieval and web search algorithms, pattern recognition, image processing, machine learning, and data mining. Even that clusteri作者: G-spot 時間: 2025-3-26 09:11
A Comprehensive Review of Evaluation and Fitness Measures for Evolutionary Data Clustering,rdingly, data clustering has an increasing interest in various applications involving health, humanities, and industry. Assessing the goodness of clustering has been widely debated across the history of clustering analysis, which led to the emergence of abundant clustering evaluation measures. The a作者: 謙卑 時間: 2025-3-26 15:04
A Grey Wolf-Based Clustering Algorithm for Medical Diagnosis Problems,ation algorithms is the Grey Wolf Optimizer (GWO). In this chapter, we use GWO on seven medical data sets to optimize the initial clustering centroids represented by the individuals of each population at each iteration. The aim is to minimize the distances between instances of the same cluster to pr作者: jeopardize 時間: 2025-3-26 18:48 作者: Obstacle 時間: 2025-3-26 22:48
,Capacitated Vehicle Routing Problem—A New Clustering Approach Based on Hybridization of Adaptive Pasts. However, no standard method has been established yet to obtain optimal solutions for all standard problems. In this research, we propose a two-phase approach: An improved k-Means algorithm for the clustering phase and a hybrid meta-heuristic based on Adaptive Particle Swarm—PSO and Grey Wolf Op作者: Chauvinistic 時間: 2025-3-27 04:40
A Hybrid Salp Swarm Algorithm with ,-Hill Climbing Algorithm for Text Documents Clustering, of documents that make pattern recognition, information retrieval, and text mining more complicated. This problem is known as a text clustering problem (TCD). Several metaheuristic optimization algorithms have been adapted to address TDC optimally. A new efficient metaheuristic optimization algorit作者: GNAW 時間: 2025-3-27 08:37
Controlling Population Diversity of Harris Hawks Optimization Algorithm Using Self-adaptive Clusterblems. HHO algorithm processes a population of search space with two operations: Soft besiege and Hard besiege. One of main problems in the use of population-based algorithms is premature convergence. A premature stagnation of the search creates a shortage of diversity, which affects the relationshi作者: MUTED 時間: 2025-3-27 12:45 作者: 羊欄 時間: 2025-3-27 16:33 作者: 委托 時間: 2025-3-27 18:31 作者: 虛弱的神經(jīng) 時間: 2025-3-27 22:28 作者: 因無茶而冷淡 時間: 2025-3-28 05:09
Book 2021eta-hill climbing optimization. The book also covers applications of evolutionary data clustering indiverse fields such as image segmentation, medical applications, and pavement infrastructure asset management..作者: Liability 時間: 2025-3-28 09:53 作者: 虛弱的神經(jīng) 時間: 2025-3-28 13:18 作者: 場所 時間: 2025-3-28 14:34 作者: 捐助 時間: 2025-3-28 21:03 作者: SMART 時間: 2025-3-28 23:27
EEG-Based Person Identification Using Multi-Verse Optimizer as Unsupervised Clustering Techniques,worth mentioning that this work is one of the first to employ optimization methods with unsupervised clustering methods for person identification using EEG. As a conclusion, the MVO algorithm achieved the best results compared with GA, PSO and .-means. Finally, the proposed method can draw future di
