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NTCI 2023 : International Conference on New Trends in Computational Intelligence


When Nov 3, 2023 - Nov 5, 2023
Where Qingdao, China
Submission Deadline Sep 15, 2023
Notification Due Sep 30, 2023
Final Version Due Oct 10, 2023
Categories    neural networks   evolutionary computation   explainable ai   computational finance

Call For Papers

The International Conference on New Trends in Computational Intelligence (NTCI 2023) will be held in Qingdao, China during November 3-5, 2023. Following the successes of previous events, NTCI 2023 aims to bring top researchers and practitioners working in different facets of computational intelligence (CI) under one umbrella to share their knowledge and enable mutual exchange of information. The conference will feature plenary speeches given by world-renowned scholars, regular sessions with broad coverage, and special sessions focusing on popular topics.

Call for Papers and Special Sessions
Prospective authors are invited to contribute high-quality papers to NTCI 2023. In addition, proposals for special sessions within the technical scope of the conference are solicited. Special sessions, to be organized by internationally recognized experts, aim to bring together researchers on special focused topics. A special session proposal should include the session title, a brief description of the scope and motivation, names, contact information, and brief biographical information on the organizers. Researchers interested in organizing special sessions are invited to submit formal proposals to

Topic Areas

Feedforward neural networks
Recurrent neural networks
Self-organizing maps
Radial basis function networks
Attractor neural networks and associative memory
Modular networks
Fuzzy neural networks
Spiking neural networks
Reservoir networks (echo-state networks, liquid-state machines, etc.)
Large-scale neural networks
Other topics in artificial neural networks


Mathematical and theoretical foundations of fuzzy sets, fuzzy measures, and fuzzy integrals
Interpretable and Interactive approaches to uncertainty in AI
Fuzzy data analysis, fuzzy clustering, classification and pattern recognition
Type-2 fuzzy sets, computing with words, and granular computing
Fuzzy systems design and optimization
Applications of fuzzy sets and systems, fuzzy measures and integrals
Fuzzy and uncertain information processing, information extraction, and fusion
Theory and applications of imprecise probabilities and possibilities
Neuro- and evolutionary-fuzzy systems


Ant colony optimization
Particle swarm optimization
Genetic algorithms
Differential evolution
Parallel and distributed algorithms
Meta-modeling and surrogate models
Evolutionary simulation-based optimization
Discrete and combinatorial optimization
Multi-objective evolutionary algorithms
Evolutionary computation theory
Evolutionary programming
Evolved neural networks
Evolutionary fuzzy systems
Evolved neuro-fuzzy systems


Unsupervised learning and clustering, (including PCA, and ICA)
Reinforcement learning
Probabilistic and information-theoretic methods
Support vector machines and kernel methods
EM algorithms
Mixture models, ensemble learning, and other meta-learning or committee algorithms
Bayesian, belief, causal, and semantic networks
Statistical and pattern recognition algorithms
Visualization of data
Feature selection, extraction, and aggregation
Hybrid learning methods
Deep learning
Other topics in machine learning

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