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Titlebook: Artificial Immune Systems; 11th International C Carlos A. Coello Coello,Julie Greensmith,Mario Pav Conference proceedings 2012 Springer-Ver

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發(fā)表于 2025-3-21 17:51:53 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Artificial Immune Systems
期刊簡稱11th International C
影響因子2023Carlos A. Coello Coello,Julie Greensmith,Mario Pav
視頻videohttp://file.papertrans.cn/163/162052/162052.mp4
發(fā)行地址Up-to-date results.Fast-track conference proceedings.State-of-the-art research
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Artificial Immune Systems; 11th International C Carlos A. Coello Coello,Julie Greensmith,Mario Pav Conference proceedings 2012 Springer-Ver
影響因子This book constitutes the refereed proceedings of the 11th International Conference on Artificial Immune Systems, ICARIS 2012, held in Taormia, Italy, in August 2012. The 19 revised selected papers presented were carefully reviewed and selected for inclusion in this book. In addition 4 papers of the workshop on bio and immune inspired algorithms and models for multi-level complex systems are included in this volume. Artificial immune systems (AIS) is a diverse and maturing area of research that bridges the disciplines of immunology, biology, medical science, computer science, physics, mathematics and engineering. The scope of AIS ranges from modelling and simulation of the immune system through to immune-inspired algorithms and in silico, in vitro and in vivo solutions.
Pindex Conference proceedings 2012
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A Multi-Objective Artificial Immune System Based on Hypervolumee and the hypervolume contribution. The main aim of this work is to investigate the performance of this class of algorithm with respect to approaches which are representative of the state-of-the-art in multi-objective optimization using metaheuristics. The results obtained by our proposed approach,
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A Comparative Study of Negative Selection Based Anomaly Detection in Sequence Datas in computer security. After initial enthusiasm, performance problems with the algorithm lead many researchers to conclude that negative selection is not a competitive anomaly detection technique. However, in recent years, theoretical work has lead to substantially more efficient negative selection
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A Beginner’s Guide to Systems Simulation in Immunologyd agent-based simulation. These methods, however, are still not widely adopted in immunology research. In addition, to our knowledge, there is few research on the processes for the development of simulation models for the immune system. Hence, for this work, we have two contributions to knowledge. T
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Mathematical Implementation of Interaction between Malaria and Immune Systemc to the disease, 243 million malaria cases were reported causing nearly a million of death, primarily of children under 5 year; nearly 3000 children die every day in Africa. In Brazil, Amazonia is the area that presents the highest number of cases and consequently having many cases of morbidity and
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Bait a Trap: Introducing Natural Killer Cells to Artificial Immune System for Spyware Detectionnt years, malware is evolving quickly in respect of stealth and complexity. This trend has brought a great challenge for AIS, especially when spyware emerged. To solve this problem, natural killer cells (NKs) which can lure latent viruses to expose themselves are introduced to AIS in this paper. We
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