| 书目名称 | Computational Network Application Tools for Performance Management |
| 编辑 | Millie Pant,Tarun K. Sharma,Chitresh Banerjee |
| 视频video | |
| 概述 | Discusses recent theoretical and practical issues in the field of computational networks.Highlights the latest advances using intelligent technology approaches.Addresses challenging issues like enhanc |
| 丛书名称 | Asset Analytics |
| 图书封面 |  |
| 描述 | .This book explores a range of important theoretical and practical issues in the field of computational network application tools, while also presenting the latest advances and innovations using intelligent technology approaches. The main focus is on detecting and diagnosing complex application performance problems so that an optimal and expected level of system service can be attained and maintained. The book discusses challenging issues like enhancing system efficiency, performance, and assurance management, and blends the concept of system modeling and optimization techniques with soft computing, neural network, and sensor network approaches. In addition, it presents certain metrics and measurements that can be translated into business value. These metrics and measurements can also help to establish an empirical performance baseline for various applications, which can be used to identify changes in system performance. By presenting various intelligent technologies, the book provides readers with compact but insightful information on several broad and rapidly growing areas in the computation network application domain..The book’s twenty-two chapters examine and address current an |
| 出版日期 | Book 2020 |
| 关键词 | Optimization; Modelling; Automated Systems; Performance Enhancement; Soft Computing; Computational Networ |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-32-9585-8 |
| isbn_ebook | 978-981-32-9585-8Series ISSN 2522-5162 Series E-ISSN 2522-5170 |
| issn_series | 2522-5162 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
发表于 2025-3-21 18:34:22
