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ISCBI 2027: International Symposium on Computational and Business Intelligence

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ISCBI
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Día de Entrega:
2026-08-30
Fecha de Notificación:
2026-09-30
Fecha de conferencia:
2027-02-26
Ubicación:
Macau, China
Ediciones:
Vistas: 17239   Seguidores: 1   Asistentes: 0

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50,0 / 100
Puesto n.º 1.515 de 5.650 congresos · 27% superior

N.º 80 de 337 en Minería de datos y bases de datos

Reconocimiento académico (35%) Sin datos: se puntúa con la línea base neutra de 50 —
Selectividad en la revisión (20%) Sin datos: se puntúa con la línea base neutra de 50 —
Ediciones celebradas (20%)
62
Atención de la comunidad (10%)
19
Integridad del registro público (15%)
55

Datos utilizados: Ediciones documentadas: 9 · Investigadores que lo siguen aquí: 1 · Investigadores que abrieron esta página en los últimos 24 meses: 4

Falta en el registro público: Tasas de aceptación históricas (+4,5) · Premios al mejor artículo (+2,3)
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Solicitud de Artículos

ISCBI 2027 (International Symposium on Computational and Business Intelligence) is an academic conference held in Macau, China on 2027-02-26. The paper submission deadline is 2026-08-30. Acceptance notifications are sent on 2026-09-30.

We invite submissions of original research papers for the International Symposium on Computational and Business Intelligence (ISCBI). The conference aims to bring together researchers and practitioners from academia and industry to share their latest research, ideas, and developments in the fields of Computational & Business Intelligence. 1. Business Intelligence Analysis of business intelligence applications and analytics Applications in business intelligence Business intelligence and CRM Business intelligence and market analysis and marketing Business intelligence in logistics and supply chain management Data mining Autonomous agents and multi-agent systems Case studies in business intelligence Data mining methodologies for business intelligence Business intelligence architectures Knowledge management and business intelligence Business intelligence for security analysis and fraud detection Decision making for business intelligence Statistical methods for business intelligence 2. Computational Intelligence 2.1 Neural Networks and Neural Information Processing Associative memories Computational neuroscience Connectionist theory and cognitive science Mathematical modeling of neural systems Neurodynamic optimization and adaptive dynamic programming Principal component analysis and related methods Hybrid intelligent systems Supervised, unsupervised and reinforcement learning Brain computer interface Neuroinformatics and bioinformatics Support vector machines and kernel methods Image processing Computer vision & pattern recognition Time series analysis Robotic and control applications Fraud detection Hardware implementation Real-world applications Emerging areas in neural networks 2.2 Fuzzy Systems Fuzzy information processing Fuzzy decision making Fuzzy logic and fuzzy set theory Fuzzy hybrids Fuzzy and rough data analysis Fuzzy optimization and design Fuzzy systems modeling and identification Fuzzy mathematics Fuzzy systems architectures and hardware Fuzzy image processing & pattern recognition Fuzzy control and systems Fuzzy data mining and forecasting Real-world applications Emerging areas in fuzzy systems 2.3 Evolutionary Computation Ant colony optimization Artificial immune systems Artificial life Bioinformatics and bioengineering Classifier systems Coevolution and collective behaviour Cognitive systems and applications Evolutionary combinatorial and numerical optimization Constraints and uncertainty handling Cultural algorithms Cuckoo search Differential evolution Estimation of distribution algorithms Evolutionary computation for bioinformatics Evolutionary computation in dynamic and uncertain environments Evolutionary computer vision Evolutionary data mining Evolutionary intelligent agents Evolutionary learning systems Evolutionary robotics Evolutionary techniques in economics, finance and marketing Evolvable hardware and software Evolved art and music Evolving neural networks and fuzzy systems Hybrid optimisation algorithms Memetic and hybrid algorithms Evolutionary multi-objective optimization Molecular and quantum computing Particle swarm optimization Real-world applications Representation and operators Self-adaptation in evolutionary algorithms Swarm Intelligence Theory of evolutionary computation Emerging areas in evolutionary computation
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