1.

Record Nr.

UNINA9910367253303321

Titolo

Computational Network Application Tools for Performance Management / / edited by Millie Pant, Tarun K. Sharma, Sebastián Basterrech, Chitresh Banerjee

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020

ISBN

981-329-585-6

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (269 pages)

Collana

Asset Analytics, Performance and Safety Management, , 2522-5162

Disciplina

658.404

Soggetti

Project management

Industrial management—Environmental aspects

Artificial intelligence

Computer organization

Computer software—Reusability

Project Management

Sustainability Management

Artificial Intelligence

Computer Systems Organization and Communication Networks

Performance and Reliability

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Performance Enhanced Hybrid Memetic Framework for Effective Coverage Based Test Case Optimization -- An Optimization Procedure for Quadratic Fractional Transportation Problem -- A Nature Inspired PID like Fuzzy Knowledge Based Fractional Order Controller for Optimization -- Neuro-Fuzzy-Rough Classification for Increasing Efficiency and Performance in Case-Based Reasoning Retrieval -- Better Performance of Human Action Recognition from Spatiotemporal Depth Information Features Classification -- Selecting Appropriate Multipath Routing In Wireless Sensor Networks for Improvisation of System’s Efficiency and Performance -- A Classification of ECG Arrhythmic Analysis Based on Performance Factors using Machine Learning Approach -- A Time Efficient Semi Automatic Active Contour Model of



Liver Tumor Segmentation from CT Images -- Denoising 1d Signal Using Wavelets for Signal Quality Enhancement.

Sommario/riassunto

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 and future research topics in areas like neural networks, soft computing, nature-inspired computing, fuzzy logic and evolutionary computation, machine learning, smart security, and wireless networking, and cover a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book was written to serve a broad readership, including engineers, computer scientists, management professionals, and mathematicians interested in studying tools and techniques for computational intelligence and applications for performance analysis. Featuring theoretical concepts and best practices in computational network applications, it will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of soft computing, neural networks, machine learning, sensor networks, smart security, etc.