A5036119057- Artificial Immune Systems Applications
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
- Advanced Clustering Algorithms Research
- T-cell and B-cell Immunology
- Gene Regulatory Network Analysis
- Vehicle Routing Optimization Methods
- Face and Expression Recognition
- Data Stream Mining Techniques
- Advanced Text Analysis Techniques
- Complex Network Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Data Mining Algorithms and Applications
- Gene expression and cancer classification
- Fuzzy Logic and Control Systems
- Image Processing Techniques and Applications
- Advanced Algorithms and Applications
- Bioinformatics and Genomic Networks
- Topic Modeling
- Mental Health via Writing
- vaccines and immunoinformatics approaches
- Computability, Logic, AI Algorithms
- Recommender Systems and Techniques
- Spam and Phishing Detection
Universidade Estadual de Campinas (UNICAMP)
2001-2025
Florida Gulf Coast University
2023-2024
Universidade de São Paulo
2023-2024
Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo
2024
Universidade Presbiteriana Mackenzie
2014-2023
Universidade Católica de Santos
2004-2016
Saarland University
2007
Carnegie Mellon University
2007
Indiana University Bloomington
2007
University of Sussex
2007
The clonal selection principle is used to explain the basic features of an adaptive immune response antigenic stimulus. It establishes idea that only those cells recognize antigens (Ag's) are selected proliferate. subject affinity maturation process, which improves their selective Ag's. This paper proposes a computational implementation explicitly takes into account response. general algorithm, named CLONALG, derived primarily perform machine learning and pattern recognition tasks, then it...
This paper presents the adaptation of an immune network model, originally proposed to perform information compression and data clustering, solve multimodal function optimization problems. The algorithm is described theoretically empirically compared with similar approaches from literature. main features include: automatic determination population size, combination local global search (exploitation plus exploration fitness landscape), defined convergence criterion, capability locating...
Multimodal optimization algorithms inspired by the immune system are generally characterized a dynamic control of population size and diversity maintenance along search. One most popular proposals is denoted opt-aiNet (artificial network for optimization) extended here to deal with time-varying fitness functions. Additional procedures designed improve overall performance robustness immune-inspired approach, giving rise version optimization, dopt-aiNet. Firstly, challenging benchmark problems...
This paper presents a new proposal for data clus-tering based on the particle swarm optimization (PSO) algorithm. The human tendency of adapting its behavior due to influence environment minimizing differences in opinions and ideas through time taking into account past experiences characterizes an emergent social behavior. In PSO algorithm, each individual population searches solution best certain neighborhood own as well. present work, algorithm was adapted position prototypes (particles)...